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DOE OSTI2022

Spatial and Temporal Characterization of Activity in Public Space, 2019–2020

The data reported here characterize spatial and temporal variation in the ratio of short-to-long-duration visits in public places (i.e., points of interest) in the United States for each week between January 2019 and December 2020. The underlying data on anonymized and aggregated foot traffic to public places is curated by SafeGraph, a geospatial data provider. In this work, we report the estimated number and duration of “short” (i.e., <4 hours) and “long” (i.e., >4 hours) visits to public places at the US census block group level. Long visits are shown to be a good proxy for workers based on formal economic data. We propose that short visits are more likely to represent nonobligate activities: people visiting a public place for leisure, shopping, entertainment, or civic or cultural engagement. Our work constructs a ratio of short to long visits, which can be used to inform population estimates for nonworker use of public space. These data may be useful for understanding how people’s use of public space has changed during the COVID-19 pandemic and, more generally, for understanding activity patterns in public.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

LandScan Global 30 Arcsecond Annual Global Gridded Population Datasets from 2000 to 2022

Abstract Oak Ridge National Laboratory (ORNL) annually develops the LandScan Global (LSG) dataset, a 30 arcsecond global gridded population dataset representing global ambient human population distribution. This multivariable dasymetric model disaggregates census counts within administrative boundaries using ancillary data. Each country’s distribution reflects cultural and socioeconomic patterns; manual validations yield a unique global dataset for assessing populations at risk. For over two decades, LSG has been a standard for estimating populations at risk, aiding U.S. federal government, academia and humanitarian organizations. During disasters such as the 2004 Indian Ocean tsunami and the 2010 Haiti earthquake and geopolitical crises such as the Syrian civil war and the 2022 Russian invasion of Ukraine, LSG supported scientific and operational communities in emergency response and recovery. In 2022, LSG datasets from 2000 onward were made publicly available through ORNL’s LandScan Portal. This data descriptor details our methodology and the application of geospatial science and machine learning to geographic and demographic data, highlighting uses in urban resiliency, emergency management, disaster response, and human health and security.

Science & Technology - Other Topics↗

DOE OSTI2025

ORBITaL-Net: A labeled training library for large-scale building feature extraction

Over the course of several years, nearly 1.5 million building outlines have been created from approximately 128,000 training tiles covering roughly 7,000 km 2 of very high-resolution multispectral overhead imagery, primarily dated between 2010 and 2020. This dataset, dubbed the Oak Ridge Building Image and TrAining Label Net (ORBITaL-Net), is designed for machine learning applications and is global in scope, with samples drawn from 72 countries across North America, South America, Africa, Europe, and Asia. ORBITaL-Net captures a great diversity in geographic setting, structural characteristics, land use (urban and rural), terrain, and imagery conditions. While the labeled building outlines are themselves valuable, the dataset’s true strength lies in the pairing of these labels with corresponding reference imagery, which is being released for open source use. Similar to SpaceNet and Replicable AI For Microplanning (ramp), this building outline dataset will allow the larger computer vision community from academia, government, and industry the opportunity to develop robust, scalable, and generalizable geospatial machine learning techniques. Unlike SpaceNet and ramp, which offer high resolution labels and imagery primarily for large urban cities, ORBITaL-Net is not focused on training samples from heavily populated areas but instead aims to capture the innate variability of conditions present in both the physical environment and imagery collections.

Geography↗

DOE OSTI2021

Quantification of Dissolved O 2 in Bulk Aqueous Solutions and Porous Media Using NMR Relaxometry

Effects of dissolved paramagnetic oxygen (O 2 ) in water on 1 H nuclear magnetic resonance (NMR) Carr-Purcell-Meiboom-Gill (CPMG) experiments is evaluated at a 1 H Larmor frequency of 2 MHz. Dissolution of O 2 into water significantly reduces the 1 H transverse relaxation coefficient (T 2 ). For deoxygenated water, T 2 is 3388 ms, water at ambient atmospheric conditions (7.4 mg/L O2) exhibits a T2 of 2465 ms, and dissolution of 2710 mg/L O 2 further reduces T 2 to 36 ms. The results were fit with an empirical model to facilitate prediction of T 2 times for bulk water as a function of paramagnetic oxygen concentrations in solution. Dissolved O 2 also greatly influences 1 H NMR CPMG experiments of confined water in a model system composed of Berea sandstone. For this system, 90 mg/L O 2 in H 2 O enhances T 2 relaxation of bulk water such that the relaxation time is comparable to physically confined water in the sandstone pores. Given the sensitivity of NMR T 2 coefficients to paramagnetic oxygen, low-field NMR-based characterization of fluid and porous media structure requires control of dissolved oxygen, as geospatial variation in the partial pressure of O 2 alone is expected to perturb fluid and pore relaxation times by up to 60 and 36%, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

North American boreal forests are a large carbon source due to wildfires from 1986 to 2016

Wildfires are a major disturbance to forest carbon (C) balance through both immediate combustion emissions and post-fire ecosystem dynamics. Here we used a process-based biogeochemistry model, the Terrestrial Ecosystem Model (TEM), to simulate C budget in Alaska and Canada during 1986–2016, as impacted by fire disturbances. We extracted the data of difference Normalized Burn Ratio (dNBR) for fires from Landsat TM/ETM imagery and estimated the proportion of vegetation and soil C combustion. We observed that the region was a C source of 2.74 Pg C during the 31-year period. The observed C loss, 57.1 Tg C year -1 , was attributed to fire emissions, overwhelming the net ecosystem production (1.9 Tg C year -1 ) in the region. Our simulated direct emissions for Alaska and Canada are within the range of field measurements and other model estimates. As burn severity increased, combustion emission tended to switch from vegetation origin towards soil origin. When dNBR is below 300, fires increase soil temperature and decrease soil moisture and thus, enhance soil respiration. However, the post-fire soil respiration decreases for moderate or high burn severity. The proportion of post-fire soil emission in total emissions increased with burn severity. Net nitrogen mineralization gradually recovered after fire, enhancing net primary production. Net ecosystem production recovered fast under higher burn severities. The impact of fire disturbance on the C balance of northern ecosystems and the associated uncertainties can be better characterized with long-term, prior-, during- and post-disturbance data across the geospatial spectrum. Our findings suggest that the regional source of carbon to the atmosphere will persist if the observed forest wildfire occurrence and severity continues into the future.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Pollen antigens and atmospheric circulation driven seasonal respiratory viral outbreak and its implication to the Covid-19 pandemic

Abstract The patterns of respiratory virus illness are expressed differently between temperate and tropical climates. Tropical outbreaks often peak in wet seasons. Temperate outbreaks typically peak during the winter. The prevailing causal hypotheses focus on sunlight, temperature and humidity variations. Yet no consistent factors have been identified to sufficiently explain seasonal virus emergence and decline at any latitude. Here we demonstrate close connections among global-scale atmospheric circulations, IgE antibody enhancement through seasonal pollen inhalation, and respiratory virus patterns at any populated latitude, with a focus on the US. Pollens emerge each Spring, and the renewed IgE titers in the population are argued to terminate each winter peak of respiratory illness. Globally circulated airborne viruses are postulated to subsequently deposit across the Southern US during lower zonal geostrophic winds each late Summer. This seasonally refreshed viral load is postulated to trigger a new influenza outbreak, once the existing IgE antibodies diminish to a critical value each Fall. Our study offers a new and consistent explanation for the seasonal diminishment of respiratory viral illnesses in temperate climates, the subdued seasonal signature in the tropics, the annually circulated virus phenotypes, and the northerly migration of influenza across the US every year. Our integrated geospatial and IgE hypothesis provides a new perspective for prediction, mitigation and prevention of the outbreak and spread of seasonal respiratory viruses including Covid-19 pandemic.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Assessing the deployment of solar-driven hydrogen from biomass at scale in the U.S.

Solar hydrogen from biomass gasification is a promising technology to sustainably produce hydrogen, responsibly dispose biomass waste, and reduce reliance on fossil fuels. However, its large-scale deployment faces challenges due to the geospatial misalignment between biomass resources and solar intensity, which introduces additional supply chain logistics costs. We analyze the logistics cost burden imposed by this misalignment and its impact on successful large-scale deployment of solar-driven hydrogen from biomass in the United States. We also consider associated carbon emissions and explore how the mix of deployed technologies evolves under externally imposed carbon penalties. Our findings show that while economies of scale are known to apply at the processing facility level, the reverse effect occurs at the broader systems-level, driven by logistics. Also, at current technology costs, high carbon penalties would be required to favor deployment of solar based technologies over conventional and hybrid alternatives. We further illustrate strategies and system-level changes to reduce logistics costs and enable sustainable, low-cost hydrogen for decarbonizing different industrial sectors.

Iloeje, Chukwunwike O. [Argonne National Laborator↗

DOE OSTI2022

Regional economic potential for recycling consumer waste electronics in the United States

Waste electronics are a growing environmental concern but also contain materials of great economic value. If properly recycled, waste electronics could enhance the sustainability of vital metal supply chains by offsetting the increasing demand for virgin mining. However, rapid changes in the size and composition of electronics complicate their end-of-life management. Here we couple material flow and geospatial analyses on over 90 critical consumer electronic products and find that over 1 billion devices, representing up to 1.5 million tonnes of mass, could be discarded annually in the United States by 2033. Emerging electronics such as connected home, health and augmented/virtual reality devices have become the fastest-growing types in the waste stream. Here we highlight policy opportunities to develop various sustainable circularity strategies around metal supply chains by showing the potential to integrate waste electronics and virgin mining pathways in western US regions, while new infrastructure designed specifically for waste electronics treatment is favourable in the central and eastern United States. Furthermore, we show the importance of building national-level refining and tear-down databases to improve electronics end-of-life management in the next decade.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Collaborative energy and land use planning

Energy models make projections for infrastructure, yet struggle to map deployment pathways at the ground level, where risks and benefits to human and natural systems materialize. Furthermore, a study now shows how blending in geospatial science can help to preserve natural capital while allowing for new infrastructure to be built.

Energy and society↗

DOE OSTI2025

More land is needed for solar and wind infrastructure under a high renewables scenario in the Western US by 2050

Expanding United States electricity infrastructure to meet growing demand could require extensive power plant development footprints and land use conversion, depending on the mix of generation types chosen. Understanding where future power plant sitings are likely to take place and identifying potential conflicts and land-use tradeoffs will be key to identifying feasible and affordable investments and evaluating regional planning coordination needs. Here we use an integrated modeling framework that combines capacity expansion planning, hourly grid operations, and geospatial techno-economic analysis to develop projections (2025-2050) of power plant sitings in the Western United States (US) at a 1 km 2 resolution for a business-as-usual scenario and a high renewables penetration scenario. We find that 30% more land will be needed in the high renewables scenario as compared to business-as-usual, and that 75% of that development is projected to be located within 10 km of natural areas.

Mongird, Kendall [Pacific Northwest National Labor↗

DOE OSTI2025

Benchmarking greenhouse gas emissions from US wastewater treatment for targeted reduction

Here, in this study, to assess the national climate impact of wastewater treatment and inform decarbonization, we assembled a comprehensive greenhouse gas inventory of 15,863 facilities in the contiguous USA. Considering location and treatment configurations, we modelled on-site CH 4 , N 2 O and CO 2 production and emissions associated with energy, chemical inputs and solids disposal. Using Monte Carlo simulations, we estimated median national emissions at 47 million tonnes of CO 2 equivalent per year, with on-site process CH 4 and N 2 O emissions exceeding current government estimates by 41%. Treatment configurations with anaerobic digesters are responsible for 16 million tonnes of CO 2 equivalent per year of fugitive methane, outweighing benefits achieved through on-site electricity generation. Systems designed for nutrient removal have the highest greenhouse gas emissions intensity, attributable to energy requirements and N 2 O production, demonstrating current trade-offs between meeting water quality and climate objectives. We analysed key sensitivities and included a geospatial analysis to highlight the scale and distribution of opportunities for reducing life cycle greenhouse gas emissions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Geographic Information System Mapping Tool for Rainwater Harvesting in the United States

The Rainwater Harvesting Tool is a publicly available web-based geographic information system tool developed using geospatial analysis in combination with historic ZIP Code level monthly average precipitation and evapotranspiration data across the United States to help select potential locations for harvesting rainwater. Rainwater harvesting can provide a key source of alternative water for a variety of uses including landscape irrigation, vehicle wash, cooling tower makeup, dust suppression, and toilet flushing. Rainwater harvesting can help support institutional, commercial, and residential buildings in diversifying water sources and offset the use of freshwater. This tool aims to help organizations strategically target locations to implement rainwater harvesting systems. The metric used in the tool is called the rainwater harvesting potential, which is a normalized metric, measured in inches per year. The rainwater harvesting potential describes the amount of rainwater that can be reasonably collected and stored at a specific location. This metric was used to rank areas delineated by ZIP Codes across the US, from lowest to highest to show the relative availability of rainwater for harvesting. Two mapping layers are included in the tool that show the general rainwater harvesting potential for all applications and a layer that specifically shows the potential for harvesting rainwater to supply irrigation The Rainwater Harvesting Tool allows users to view overall trends across the United States, while also allowing the user to zoom in to a scale where ZIP Code boundaries are clearly delineated. The tool can be used to help organizations with buildings located in multiple regions to strategically identify where to install rainwater harvesting systems and prioritize locations that may be optimal for rainwater harvesting.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Statistical moments of VIIRS night-time lights

Annual VIIRS global night-time lights traditionally report mean radiance levels after filtering to remove moonlit and cloudy data followed by outlier removal. The mean is the first statistical moment, but there are three other statistical moments (variance, skew and kurtosis) that are currently not produced globally. In this study, we generated VIIRS day/night band multiyear and annual statistical moments for a widely dispersed set of test areas. The moments were calculated from 15 arc second nightly temporal profiles spanning 2012-2020, filtered to exclude cloudy and sunlit data, with radiance adjustments to reduce view angle and lunar illuminance effects. The moment data were examined in two ways: (1) Geospatial grids-which reveal zonation and temporal changes present in urban areas and (2) Scattergrams of moment pairs. The variance versus mean scattergram exhibits several distinct data clusters used to define five zones: core lighting, dark-erratics, mid-erratics, bright-erratics and bright and seteady. The results indicate that the information content of VIIRS night-time lights can be augmented if all four statistical moments are calculated.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Applying the index of watershed integrity to the Matanuska–Susitna basin

The Matanuska-Susitna Borough is the fastest growing region in the State of Alaska and is impacted by a number of human activities. We conducted a multiscale assessment of the stressors facing the borough by developing and mapping the Index of Watershed Integrity (IWI) and Index of Catchment Integrity (the latter considers stressors in areas surrounding individual stream segments exclusive of upstream areas). The assessment coincided with the borough’s stormwater management planning. We adapted the list of anthropogenic stressors used in the original conterminous United States IWI application to reflect the borough’s geography, human activity, and data availability. This analysis also represents an early application of the NHDPlus High Resolution geospatial framework and the first use of the framework in an IWI study. We also explored how remediation of one important stressor, culverts, could impact watershed integrity at the catchment and watershed scales. Overall, we found that the integrity scores for the Matanuska– Susitna basin were high compared to the conterminous United States. Low integrity scores did occur in the rapidly developing Wasilla–Palmer core area. We also found that culvert remediation had a larger proportional impact in catchments with fewer stressors.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

A five-year milestone: reflections on advances and limitations in GeoAI research

The Annual Meeting of the American Association of Geographers (AAG) in 2023 marked a five-year milestone since the first Geospatial Artificial Intelligence (GeoAI) Symposium was held at AAG in 2018. In the past five years, progress has been made while open questions remain. In this context, we organized an AAG panel and invited five panellists to discuss the advances and limitations in GeoAI research. The panellists commended the successes, such as the development of spatially explicit models, the production of large-scale geographic datasets, and the use of GeoAI to address real-world problems. The panellists also shared their thoughts on limitations in current GeoAI research, which were considered as opportunities to engage theories in geography, enhance model explainability, quantify uncertainty, and improve model generalizability. This article summarizes the presentations from the panellists and also provides after-panel thoughts from the organizers. We hope that this article can make these thoughts more accessible to interested readers and help stimulate new ideas for future breakthroughs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Quantifying the compound hazard of freezing rain and wind gusts across CONUS

Abstract The co-occurrence of freezing rain, ice accumulation and wind gusts (FZG) poses a significant hazard to infrastructure and transportation. However, quantification of the frequency and intensity of FZG is challenged by the lack of direct icing measurements. In this work, we evaluate and then apply an energy balance model to high-frequency data collected during 2005–2022 to derive hourly ice accumulation at 883 stations across the contiguous USA. These estimates are combined with wind gust observations to compute time series of hourly FZG hazard magnitude using the Sperry–Piltz Ice Accumulation (SPIA) index. Results are evaluated using Storm Reports of damage and economic disruption. The hourly SPIA estimates are also used to (i) derive a geospatial atlas of the hazard including the 50 yr return period event intensities for each US state derived using superstations, and (ii) describe storylines of significant events in terms of meteorological drivers and socioeconomic impacts. The highest values of SPIA during the 18 yr study period occur in a region extending from the Southern Great Plains over the Midwest into the densely populated Northeast. States in these regions also have high 50 yr return period maximum radial ice accumulation of 3–5 cm and co-occurring wind gusts >30 ms −1 . These values are comparable to past estimates for the 500 yr event which may imply this hazard has been previously underestimated. This atlas can be used to inform optimal FZG hazard mitigation strategies for each state/region.

58 GEOSCIENCES↗

DOE OSTI2026

Analyzing Land Characteristics Associated with Historical Large-Scale Solar Photovoltaic Deployment in the United States

Large-scale solar (LSS) deployment has accelerated rapidly across the United States, yet comprehensive understanding of its siting patterns remains limited. Here, we present a national-scale geospatial assessment of land characteristics converted for LSS development and apply statistical analyses to evaluate whether installations are disproportionately concentrated within specific land types. We find that siting patterns are strongly correlated with high solar irradiance, underscoring the role of resource quality in shaping deployment decisions. LSS projects are disproportionately concentrated on agricultural lands and shrubland. Within agricultural areas, installations predominantly occur on croplands and are strongly associated with irrigated systems. Notably, more than 90% of projects are deployed on agricultural land with Productive, Versatile, and Resilient (PVR) index values of land quality exceeding the national median. These findings highlight the need for strategic siting frameworks that reconcile solar development with the conservation of agriculturally valuable land.

14 SOLAR ENERGY↗

DOE OSTI2022

Recovering Rare Earth Elements from Coal Mine Drainage Using Industrial Byproducts: Environmental and Economic Consequences

Coal mine drainage (CMD) impairs tens of thousands of kilometers of U.S. waterways each year, in part with the leaching of low concentrations of rare earth elements (REEs). REEs are essential for modern technologies, yet economically viable natural deposits are geospatially limited, thus engendering geopolitical concerns, and their mining is energy intense and environmentally destructive. This work summarizes laboratory-scale experimentalresults of a trap-extract-precipitate (TEP) process and uses the mass and energy balances to estimate the economic costs and environmental impacts of the TEP. The TEP process uses the alkalinity and filtering capacity of stabilized flue gas desulfurization (sFGD) material or water treatment plant (WTP) sludge to remediate CMD waters and extract REEs. Passive treatment systems that use WTP sludge are cheaper than those that use sFGD material ($\$$89,300/year or $\$$86/gT-REE vs. $\$$89,800/year or $\$$278/gT-REE) and have improved environmental performance across all indicators from two different impact assessment methods. These differences are largely attributable to the larger neutralizing capacity of WTP sludge in the treatment application.

01 COAL, LIGNITE, AND PEAT↗