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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

gamut: A Geospatial R Package to Analyze Multisectoral Urban Teleconnections

Most cities in the United States withdraw surface water to meet public water supply needs. The lands on which this water is generated are often developed for human activities -- such as agriculture, mining, and industry -- that may compete for water resources or contaminate water supplies. Cities are thereby connected to other sectors through their water supply catchments. This connection is an example of an multisectoral urban teleconnection. The Geospatial Analytics for Multisectoral Urban Teleconnections (``gamut``) package provides national-scale information on these teleconnections by combining land use data with hydrological analysis to characterize urban source watershed human interactions across the conterminous United States.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology Using Large Language Models—A Case in Optimizing Intermodal Freight Transportation

The incorporation of Artificial Intelligence (AI) models into various optimization systems is on the rise. However, addressing complex urban and environmental management challenges often demands deep expertise in domain science and informatics. This expertise is essential for deriving data and simulation-driven insights that support informed decision-making. In this context, we investigate the potential of leveraging the pre-trained Large Language Models (LLMs) to create knowledge representations for supporting operations research. By adopting ChatGPT-4 API as the reasoning core, we outline an applied workflow that encompasses natural language processing, Methontology-based prompt tuning, and Generative Pre-trained Transformer (GPT), to automate the construction of scenario-based ontologies using existing research articles and technical manuals of urban datasets and simulations. From these ontologies, knowledge graphs can be derived using widely adopted formats and protocols, guiding various tasks towards data-informed decision support. The performance of our methodology is evaluated through a comparative analysis that contrasts our AI-generated ontology with the widely recognized pizza ontology, commonly used in tutorials for popular ontology software. We conclude with a real-world case study on optimizing the complex system of multi-modal freight transportation. Our approach advances urban decision support systems by enhancing data and metadata modeling, improving data integration and simulation coupling, and guiding the development of decision support strategies and essential software components.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Modeling Green Roof Potential to Mitigate Urban Flooding in a Chinese City

The Middle and Lower Reaches of the Yangtze River (MLRYR) region, which has humid subtropical climate conditions and unique plum rain season, is characterized by a simultaneous high-frequency urban flooding and reduction in groundwater levels. Retrofitting the existing buildings into green roofs is a promising approach to combat urban flooding, especially for a densely developed city. Here, the application potential of the Green Roof System (GRS) and the Improved Green Roof System (IGRS) designed to divert overflowing water from green roofs to recharge groundwater were analyzed in a densely developed city, Nanchang, China. For the first time, the influence of GRS on the hydraulic condition of Combined Sewage System/Storm Water System (CSS/SWS) is analyzed, which is a direct reflection of the effect of GRS on alleviating urban flooding. The simulation results show that GRS can retain about 41–75% of precipitation in a 2-hour timescale and the flooding volumes in the GRS/IGRS region are 82% and 28% less than those of the Traditional Roof System (TRS) in 10- and 100-yr precipitation events, respectively. In the continuous simulations, GRS also enhances Evapotranspiration (ET), which accounts for 39% of annual precipitation, so that reduces the cumulative surface runoff. Considering the IGRS can provide more hydrological benefits than the GRS under the same climate conditions, we may conclude that the widespread implementation of both the GRS and the IGRS in Nanchang and other densely developed cities in the MLRYR region could significantly reduce surface and peak runoff rates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Impact of Mixed Sources on the Atmospheric Aerosols of Urbanized Areas in the Philippines

Southeast Asia (SEA) holds approximately 10% of the global population, who are constantly exposed to severe local and transboundary air pollution. Here, we characterized the physiochemical characteristics of atmospheric aerosols in urbanized areas (Valenzuela, Manila, and Boracay) in the Philippines. The variability of coarse and fine aerosols, black carbon (BC), and trace elements of particulate matter (PM) were analyzed between June 2017 and April 2019. The average fine (coarse) aerosols of Valenzuela, Manila, and Boracay were 26.7 (80.4), 27.9 (86.6), and 20.9 (124.6) µg m –3 , respectively, which all exceeded the recent annual limits of the World Health Organization. The average BC level was 6.6 µg m –3 across three sampling sites, ranging between 4 to 83% of the fine PM mass. Vehicular emission predominated at the extreme urban sites as reflected by the high BC levels attributed to transport activities. The conventional receptor modeling procedure was implemented and improved by integrating BC speciation, which distinguished vehicle emission and biomass burning. The new method revealed eight and seven sources influencing the atmospheric conditions of Valenzuela and Boracay. In particular, the elevated zinc and lead highlighted the substantial impact of industrial sources in Valenzuela, attributing more than 9% of PM 2.5 . For Boracay, construction activities evidently enhanced PM based on the mass burden of calcium. Overall, the results uncovered the origin of PM 2.5 in urbanized locations in the Philippines, which will be valuable in reducing the exposure of a significant portion of the global population to harmful pollutants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dynamic integration of GCAM-Demeter and CLUBS-Select: Datasets on urban extensification effects on land cover, crop yields, net primary production, and CO2 emissions

The datasets provide background data from McManamay et al. (2024) Nature Communications Earth and Environment. We integrate projected dynamic non-urban lands from GCAM-Demeter with projected dynamic urban lands from SELECT from 2015 to 2100 at 1-km resolution to examine stress to the land system, compromised crop production, and losses in Net Primary Production (NPP), that can arise from the competition over land resources. These datasets include changes to non-urban land use and land cover, estimated losses in crop yields, losses in NPP, and increases in CO2 emissions.

Earth Systems↗
DOE OSTI2026

Community-Informed Urban Flood Modeling for Impact Mitigation

Climate change is intensifying the hydrologic cycle, leading to more frequent and severe rainfall-driven (pluvial) flooding in urban areas. In the mid-Atlantic US cities, aging and under-designed stormwater infrastructure is increasingly strained by these events, resulting in recurring damage to property and disruptions to transportation networks. In this study, we combine community engagement with hydrologic modeling to develop and evaluate potential urban flood adaptation strategies. Over a three-year period, local technical experts and community representatives met regularly to discuss flooding concerns, identify priorities, and co-develop adaptation strategies. These discussions informed the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed, the focus location of this study. The flooding model integrates complex surface and subsurface stormwater infrastructure data, local expert knowledge, and community insights. We simulate stakeholder-prioritized adaptations, such as green and gray infrastructure strategies. Model results demonstrate that enhanced infrastructure maintenance is the most effective adaptation for reducing flood depths, but has varied effects across the watershed, and can increase flooding in some locations. Spatially concentrated greening provides limited benefit to the watershed as a whole, but moderate benefit in community priority areas. Together, these adaptations have the potential to reduce flood depths by as much as 58% in some locations, greatly reducing property damage and mobility impacts, primary concerns of stakeholders. Future work will implement robust optimization tools to search for adaptations which meet stakeholder objectives and perform highly under varied future climate conditions. This work contributes to the expanding literature on collaborative modeling and demonstrates that community-engaged approaches can enhance model credibility and generate more actionable insights for communities seeking to strengthen climate resilience.

Baltimore MD↗
DOE OSTI2022

Automated Mobility Platforms: A Framework for Versatile, Energy-Efficient Urban Transportation for the 21st Century: Preprint

This paper presents automated mobility platforms (AMPs) as a framework to deliver high-quality urban mobility. AMPs leverage advances in sensing technology developed from automated roadway vehicles to provide opportunities for efficient movement of people and goods in dense urban environments, campuses, and large facilities like airports. In this paper, we layout the concept of AMPs and how they can serve the mobility needs of the population by providing service at the intersection of micromobility (services such as electric scooters or bikes), personal rapid transit, and moving walkways. Several key attributes and justification for the AMPs concept are described, including improvements to accessibility (inherent in design) covering both socioeconomic and disability equity, safety, energy efficiency, cost-effectiveness, urban land and space management, and scalability. We summarize the results from an ongoing national laboratory-sponsored, faculty-supported, student-led investigation into AMPs that includes stakeholder engagement and technical feasibility assessment.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Integrated Urban Services (IUS) Pilot Project Profile - Integrated AgriTech Hub Development in Flagship F Zone: Iskandar Malaysia

This brief provides a project snapshot of the Integrated Urban Services program's support to Iskandar Malaysia for development of an integrated urban agricultural hub. Integrated Urban Services is a U.S. State Department program launched in 2021 under the United States-Association of Southeast Asian Nations Smart Cities Partnership helping cities build resilience in their energy, food, and water provisioning systems.

ASEAN↗
DOE OSTI2025

Mitigating urban climate-energy feedback with citywide building-integrated photovoltaics implementation

Urban heat islands (UHIs) intensify cooling demands, whose waste heat further exacerbates UHI, creating a self-reinforcing feedback loop. Building-integrated photovoltaics (BIPV) can break this cycle by generating electricity and altering urban climate-energy interactions, yet its net impact remains unresolved. Using a cross-scale modeling framework for 118,521 buildings in Hong Kong, we demonstrate that BIPV glazing reduces cooling demand through improved insulation and lower solar heat gain, while inducing diurnal thermal asymmetry of daytime warming (up to +1.9°C) and nighttime cooling (up to −2.5°C). This microclimate regulation indirectly contributes to a 0.6% reduction in citywide building energy use. Cumulative savings from electricity generation and reduced energy use reach 4.7% (2,060.2 GWh) and 10.1% (4,401.3 GWh) under low- and high-coverage deployment, respectively, with building-level savings of −20.1% ± 11.7% (mean ± SD) at high coverage. We establish BIPV as a configurable climate-energy regulator that enables net-zero, heat-resilient planning and quantifies deployment trade-offs in cooling-dominated cities worldwide.

Building-integrated photovoltaics (BIPV)↗
DOE OSTI2023

Contrasting Trends and Drivers of Global Surface and Canopy Urban Heat Islands

A comprehensive comparison of the trends and drivers of global surface and canopy urban heat islands (termed / s and / c trends, respectively) is critical for better designing urban heat mitigation strategies. However, such a global comparison remains largely absent. Using spatially continuous land surface temperatures and surface air temperatures (2003–2020), here we find that the magnitude of the global mean / s trend (0.19 ± 0.006°C/decade, mean ± SE) for 5,643 cities worldwide is nearly six-times the corresponding / c trend (0.03 ± 0.002°C/decade) during the day, while the former (0.06 ± 0.004°C/decade) is double the latter (0.03 ± 0.002°C/decade) at night. Variable importance scores indicate that global daytime / s trend is slightly more controlled by surface property, while background climate plays a more dominant role in regulating global daytime / c trend. At night, both global / s and / c trends are mainly controlled by background climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Sap Velocity Data for Urban Trees in Chicago, Illinois (2024-2025)

This dataset contains uncorrected sap velocity measurements using the heat ratio method (HRM) collected using ICT International SFM1x sensors at five urban sites in Chicago, Illinois, as part of the DOE CROCUS project. The data includes continuous monitoring of sap velocity from various tree species, including Maples (Acer spp.): Sugar Maple (Acer saccharum), Silver Maple (Acer saccharinum), and Red Maple (Acer rubrum); Oaks (Quercus spp.): Swamp White Oak (Quercus bicolor); American Elm (Ulmus americana); Honey Locust (Gleditsia triacanthos); Cottonwood (Populus deltoides); and Tree of Heaven (Ailanthus altissima) across Chicago State University (CSU), Northeastern Illinois University (NEIU), Northwestern University (NU), University of Illinois Chicago (UIC), and West Woodlawn "Blacks in Green" (BIG). These include both street trees and those in urban park locations. Measurements were collected at 15-20 minute intervals, depending on the sensor, and transmitted via Long Range Wide Area Network (LoRaWAN) protocols. The wireless data was collected by Sage Network (https://sagecontinuum.org/) nodes. The dataset includes sensor ID, Global Positioning System (GPS) coordinates, tree species (common and scientific names), tree identification number, diameter at breast height (DBH in cm), uncorrected sap velocity measurements (cm/hr) from both inner and outer probes, and Sage Node identifiers so the data can be mapped to related variables such as air quality and wind speed that were collected on the Sage nodes. All timestamps are in local Chicago time (CDT/CST). Quality control flags are provided using a 3-bit binary system indicating physical range violations (< -10 or > 60 cm/hr), step spikes (absolute difference > 36 cm/hr), and stuck sensor conditions (> 10 consecutive identical values). These are raw data, not corrected for wood anatomy or species-specific characteristics. Data is provided in comma separated (CSV) format. This dataset is part of a larger collection of CROCUS environmental monitoring data, including linked datasets from Air Quality Transmitter (AQT) sensors, Weather Transmitter (WXT) sensors, and Multi-Function Research LoRaWAN (MFR) Nodes. DOIs for the supporting data are provided as part of this data package.

Chicago↗
DOE OSTI2025

High fidelity simulations of contaminant dispersion in an urban environment with comparison to magnetic resonance imaging measurements

The dispersion of a contaminant in an urban environment has the potential to impact a large population of people. In this work, a complex urban canopy flow based on the Oklahoma City downtown business district circa 2003 is studied using Magnetic Resonance Imaging (MRI) and high-fidelity Large Eddy Simulations (LES). MRI is a novel experimental technique that can provide high-resolution measurements in four dimensions (three spatial and temporal) for lab scale models. The experiments and simulations use the same geometry and boundary conditions providing a one-to-one comparison of the two methods. Results are presented on the time-averaged velocity and concentration fields, the temporal dynamics of the concentration plumes for a transient release, and a novel Cloud Identification Algorithm that can separate plumes produced by periodic contaminant releases used for ensemble averaging over many releases. The MRI and LES datasets both include millions of measurement voxels and the comparisons highlight the complex 3D nature of the flow including strong vertical velocities in spanwise street canyons and flow acceleration in streamwise street canyons. The concentration fields are qualitatively similar albeit the LES shows larger dispersion. A quantitative analysis with performance measures compares the datasets pointwise and demonstrates that the two 3D datasets are similar with respect to many measures including a fractional bias of 0.02 (ideal=0.0), correlation coefficient of 0.87 (ideal = 1.0), and the fraction points within a factor of 2 is 0.98 (ideal = 1.0). Plume analysis compares the arrival and residence time of contaminant and is found to vary significantly with location within the urban environment with arrival times between 0 and 1.25 and differences within the contaminant cloud less than 10% at most locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Framework for optimization of long-term, multi-period investment planning of integrated urban energy systems

In order to achieve stringent greenhouse gas emission reductions, a transition of our entire energy system from fossil to renewable resources needs to be designed. Such an energy transition brings two main challenges: most renewables generate variable electric energy, yet most demand is currently not electric (carrier mismatch) and does not always manifest at the same time as supply (temporal mismatch). Integrating multiple energy infrastructures can address both challenges by using the synergy between different energy carriers; building on existing infrastructure, while allowing a robust and flexible integration of the new. This paper proposes an optimization framework for long-term, multi-period investment planning of urban energy systems in an integrated manner. We formulate it as a mixed-integer linear program, combining a capacitated facility location with a multi-dimensional, capacitated network design problem. It includes generation and network expansion planning as well as interconnections between networks and storage infrastructure for each energy system. It can incorporate pathway effects like techno-economic developments, policy measures, and weather variations. The intended use is to support urban decision makers with long-term investment planning, though it can be tailored to fit other geographical or temporal scales. We demonstrate the model using two cases based on an average city in The Netherlands, which wants to reduce its CO 2 -emissions with 95% by 2050. In the first case, we include explicit carbon-emission constraints to study the effects of the carrier mismatch. In the second case, we implement interannual weather variations to analyze the temporal mismatch. The results give valuable insights into the energy transition design strategy for urban decision makers. They also show the future potential, as well as the computational challenges of the optimization framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Long-term trends in urban NO 2 concentrations and associated paediatric asthma incidence: estimates from global datasets

Combustion-related nitrogen dioxide (NO 2 ) air pollution is associated with paediatric asthma incidence. We aimed to estimate global surface NO 2 concentrations consistent with the Global Burden of Disease study for 1990-2019 at a 1 km resolution, and the concentrations and attributable paediatric asthma incidence trends in 13 189 cities from 2000 to 2019. We scaled an existing annual average NO 2 concentration dataset for 2010-12 from a land use regression model (based on 5220 NO 2 monitors in 58 countries and land use variables) to other years using NO 2 column densities from satellite and reanalysis datasets. We applied these concentrations in an epidemiologically derived concentration-response function with population and baseline asthma rates to estimate NO 2 -attributable paediatric asthma incidence. We estimated that 1.85 million (95% uncertainty interval [UI] 0.93-2.80 million) new paediatric asthma cases were attributable to NO 2 globally in 2019, two thirds of which occurred in urban areas (1.22 million cases; 95% UI 0.60-1.8 million). The proportion of paediatric asthma incidence that is attributable to NO 2 in urban areas declined from 19.8% (1.22 million attributable cases of 6.14 million total cases) in 2000 to 16.0% (1.24 million attributable cases of 7.73 million total cases) in 2019. Urban attributable fractions dropped in high-income countries (-41%), Latin America and the Caribbean (-16%), central Europe, eastern Europe, and central Asia (-13%), and southeast Asia, east Asia, and Oceania (-6%), and rose in south Asia (+23%), sub-Saharan Africa (+11%), and north Africa and the Middle East (+5%). The contribution of NO 2 concentrations, paediatric population size, and asthma incidence rates to the change in NO 2 -attributable paediatric asthma incidence differed regionally. Despite improvements in some regions, combustion-related NO 2 pollution continues to be an important contributor to paediatric asthma incidence globally, particularly in cities. Mitigating air pollution should be a crucial element of public health strategies for children.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Iron Speciation in PM 2.5 From Urban, Agriculture, and Mixed Environments in Colorado, USA

Atmospheric iron solubility varies depending on whether the particles are collected in rural or urban areas, with urban areas showing increased iron solubility. In this study, we investigate if the iron species present in different environments affects its ultimate solubility. Field data are presented from the Platte River Air Pollution and Photochemistry Experiment (PRAPPE), aimed at understanding the interactions between organic carbon and trace elements in atmospheric particulate matter (PM). 24-hr PM 2.5 samples were collected during the summer and winter (2016–2017), at three different sites on the Eastern Colorado plains: an urban, agricultural, and a mixed site. Downtown Denver had an average total and water-soluble iron air concentration of 181.2 and 7.7 ng m -3 , respectively. Platteville, the mixed site, had an average of total iron of 76.1 ng m -3 , with average water-soluble iron concentration of 9.1 ng m -3 . Jackson State Park (rural/agricultural) had the lowest total iron average of 31.5 ng m -3 and the lowest water-soluble iron average, 1.3 ng m -3 . The iron oxidation state and chemical speciation of 97 samples across all sites and seasons was probed by X-ray absorption near edge structure (XANES) spectroscopy. The most common iron phases observed were almandine (Fe 3 Al 2 Si 3 O 12 ) (Denver 21%, Platteville 16%, Jackson 24%), magnetite (Fe 3 O 4 ) (Denver 9%, Platteville 4%, Jackson 5%) and Fe (III)dextran (Denver 5%, Platteville 13%, Jackson 5%), a surrogate for Fe-organic complexes. Additionally, native iron [Fe(0)] was found in significant amounts at all sites. No correlation was observed between iron solubility and iron oxidation state or chemical speciation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Urban Scaling as Validation for Predictions of Imperviousness From Population

Abstract Strategies for creating quantitative projections for human systems, especially impervious surfaces, are necessary to consider the human drivers of climate and ecosystem change. There are models that generate predictions of how impervious surfaces may change in response to different potential futures, but few tools exist for validating those predictions. We seek to fill that gap. We demonstrate a statistically robust sublinear scaling relationship between population and urban imperviousness across a 15 year history. We show that Integrated Climate and Land‐Use Scenarios (ICLUS) urbanization projections are also consistent with theory. These results demonstrate a theory that can be used to validate other models' predictions of urban growth and land cover change, analogous to the ways in which allometric scaling laws in biology have been used to validate process‐based models of ecosystem composition under different climate scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Urban Effect on Precipitation and Deep Convective Systems Over Dallas‐Fort Worth

A range of multi-year observational data sets are used to characterize the hydroclimate of the Dallas Fort-Worth area (DFW) and to investigate the impact of urban land cover on daily accumulated precipitation, RADAR composite reflectivity (cREF), and cloud top height (CTH) during the warm season. Analyses of observational data indicate rainfall rates (RR) in a 45° annulus sector 50–100 km downwind of the city are enhanced relative to an upwind area of comparable size. Enhancement of mean precipitation intensity in this annulus sector is not observed on days with spatially averaged RR > 6 mm/day. Under some flow directions, the probability of cREF >30 dBZ, occurrence of hail, and the probability of CTH >10,000 geopotential meters are also enhanced up to 200 km downwind of DFW. Two deep convection events that passed over DFW are simulated with the Weather Research and Forecasting model using a range of microphysical schemes and evaluated using RADAR observations. Model configurations that exhibit the highest fidelity in these control simulations are used in a series of perturbation experiments where the areal extent of the city is varied between zero (replacement with grassland) and eight times its current size. These perturbation experiments indicate a non-linear response of Mesoscale Convective System properties to the urban areal extent and a very strong sensitivity to the microphysical scheme used. The impact on precipitation from the urban area, even when it is expanded to eight-times the current extent, is much less marked for deep convection with stronger synoptic forcing.

58 GEOSCIENCES↗
DOE OSTI2025

Prototype-Wise Sensitivity Analysis of Urban Building Energy Simulation Surrogate Modeling Accuracy

Urban Building Energy Modeling (UBEM) is an important reference for urban energy-related policymaking. Because of the significant impact of urban microclimates on the energy simulation, UBEM requires simulations of many microclimate-prototype pairs. Surrogate modeling is commonly used to reduce the cost of simulation computations. In UBEM surrogate modeling, it is important to determine the percentage of microclimates related to a prototype used for generating surrogate model training data. This study analyzes the prototype-wise variations and sensitivities of surrogate model estimation accuracy to the microclimate sampling ratios. The results of the study can help determine the number of simulations used for generating surrogate modeling data, avoid redundant simulations, and reduce the computational cost for UBEM surrogate modeling and its time.

Pan, Xiyu↗