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DOE OSTI2026

A scalable variational method for estimating the latent infection-rate field of an outbreak

In this paper, we explore whether the infection-rate of a disease can serve as a robust monitoring variable in epidemiological surveillance algorithms. The infection-rate is dependent on population mixing patterns that do not vary erratically day-to-day; in contrast, daily case-counts used in contemporary surveillance algorithms are corrupted by reporting errors. The technical challenge lies in estimating the latent infection-rate from case-counts. Here we devise a Bayesian method to estimate the infection-rate across multiple adjoining areal units, and then use it, via an anomaly detector, to discern a change in epidemiological dynamics. We extend an existing model for estimating the infection-rate in an areal unit by incorporating a Markov random field model, so that we may estimate infection-rates across multiple areal units, while preserving spatial correlations observed in the epidemiological dynamics. To carry out the high-dimensional Bayesian inverse problem, we develop an implementation of mean-field variational inference specific to the infection model and integrate it with the random field model to incorporate correlations across counties. The method is tested on estimating the COVID-19 infection-rates across all 33 counties in New Mexico using data from the summer of 2020, and then employing them to detect the arrival of the Fall 2020 COVID-19 wave. We perform the detection using a temporal algorithm that is applied county-by-county. We also show how the infection-rate field can be used to cluster counties with similar epidemiological dynamics.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

2006 Greater Triangle Household Travel Survey

The Greater Triangle Household Travel Survey was a comprehensive study of travel behavior throughout the 12-county Research Triangle Region, including all portions of Chatham, Durham, Franklin, Granville, Johnston, Lee, Orange, Person, Wake, and Vance counties, the eastern portion of Harnett County, and the southern portion of Nash County. The primary objective of this survey effort was to document demographic and travel behavior characteristics of regional travelers in order to update the current regional model and to develop a new, more robust travel demand model for the 12-county region. The 2006 survey was conducted in association with NuStats' DataSource and Louis Berger Group and was sponsored by the Capital Area Metropolitan Planning Organization, the Durham-Chapel Hill-Carrboro Metropolitan Planning Organization, the Triangle Transit Authority, and the North Carolina Department of Transportation. The project was conducted over an eleven-month period from August 2005 through June 2006. The survey utilized standard household travel survey methods, in which all household members from 5,107 households were asked to record all trips for a specified 24-hour period using a specially designed travel log on a non-holiday weekday.

1Hz data↗

DOE OSTI2026

2001 KIPDA Regional Household Travel Survey

The Kentuckiana Planning and Development Agency (KIPDA) conducted this four-month study from October 2000 through January 2001 to update regional travel demand models. The universe for the survey consisted of households in the five-county Louisville transportation planning study area, including Clark and Floyd counties in Indiana and Bullitt, Jefferson, and Oldham counties in Kentucky. Demographic variables and travel behavior characteristics were collected for 4,433 households in a 24-hour period. Of these, 4,113 were completed with households that were selected at random, and the remaining 320 were completed with representatives. The data from the survey only reflect travel by the selected residents of the five counties listed above and do not account for travel in the region by persons who were not residents of those five counties.

1Hz data↗

DOE OSTI2021

Scat Detection Dog Surveys for the San Joaquin Kit Fox on the Lawrence Livermore National Laboratory's Experimental Test Site (Site 300) and the Corral Hollow Ecological Reserve: 2020 Deployment

The San Joaquin kit fox (Vulpes macrotis mutica) historically occupied an extensive range in the San Joaquin Valley, California; however, their populations and habitat have since been significantly reduced by human impacts (United States Fish and Wildlife Service [USFWS] 1998). More than 95% of the potential habitat for kit foxes on the San Joaquin Valley floor has been converted to irrigated agriculture, urbanized, or industrialized lands. The San Joaquin kit fox was listed as endangered by the USFWS in 1967 and as threatened by the State of California in 1971. Records from local surveys, research projects, and incidental sightings indicate the present distribution of kit foxes extends from 1) southern Kern County north to Contra Costa, Alameda, and San Joaquin counties on the west side of the valley and to Stanislaus County on the east side; 2) into some of the larger, uncultivated valley-floor land parcels in Kern, Tulare, Kings, Fresno, Madera, and Merced counties; and 3) westward within 5 counties in the interior coastal range (USFWS 1998). Kit foxes have been denoted to occur in 3 geographically distinct core and several satellite populations in a heavily fragmented landscape, with the largest extant populations concentrated in the southern part of the range and smaller populations and isolated sightings in the central and northern portions (USFWS 1998, 2010).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Assessing complexity and dynamics in epidemics: geographical barriers and facilitators of foot-and-mouth disease dissemination

Introduction: Physical and non-physical processes that occur in nature may influence biological processes, such as dissemination of infectious diseases. However, such processes may be hard to detect when they are complex systems. Because complexity is a dynamic and non-linear interaction among numerous elements and structural levels in which specific effects are not necessarily linked to any one specific element, cause-effect connections are rarely or poorly observed. Methods: To test this hypothesis, the complex and dynamic properties of geo-biological data were explored with high-resolution epidemiological data collected in the 2001 Uruguayan foot-and-mouth disease (FMD) epizootic that mainly affected cattle. County-level data on cases, farm density, road density, river density, and the ratio of road (or river) length/county perimeter were analyzed with an open-ended procedure that identified geographical clustering in the first 11 epidemic weeks. Two questions were asked: (i) do geo-referenced epidemiologic data display complex properties? and (ii) can such properties facilitate or prevent disease dissemination? Results: Emergent patterns were detected when complex data structures were analyzed, which were not observed when variables were assessed individually. Complex properties–including data circularity–were demonstrated. The emergent patterns helped identify 11 counties as ‘disseminators’ or ‘facilitators’ (F) and 264 counties as ‘barriers’ (B) of epidemic spread. In the early epidemic phase, F and B counties differed in terms of road density and FMD case density. Focusing on non-biological, geographical data, a second analysis indicated that complex relationships may identify B-like counties even before epidemics occur. Discussion: Geographical barriers and/or promoters of disease dispersal may precede the introduction of emerging pathogens. If corroborated, the analysis of geo-referenced complexity may support anticipatory epidemiological policies.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1975

Soil salinity detection

The author has identified the following significant results. Growth forms and herbage biomass production varied considerably among saline and nonsaline soil range sites in Starr County. Grasses on saline soil sites were shallow-rooted and short whereas on nonsaline sites there was an intermixture of short and midgrass species. Differentiation between primarily undisturbed saline and nonsaline rangelands, in Starr County, is partially possible using film optical density readings from Skylab imagery. Differentiation among eight saline and nonsaline soil sites in Cameron County, using black and white and color film was not possible according to statistical results from both DMRT and correlation analysis. Linear analysis showed that Bendix 24-band MSS data (aircraft) collected at 1700 m and 4800 m, as well as Skylab and LANDSAT-1 MSS data, were significantly correlated to electrical conductivity readings. In Starr County, the best spectral band for detection of saline soil levels, using black and white SO-022 film, was in the 0.6 to 0.7 micron spectral region. In Cameron County, the best spectral bands for detection of saline soil levels were the 2.3 to 2.43 micron, 0.72 to 0.76 micron, 0.69 to 1.75 micron, and 0.7 to 1.1 micron spectral regions.

Wiegand, C. L.↗

NASA NTRS1981

Application of remote sensing to selected problems within the state of California

Specific case studies undertaken to demonstrate the usefulness of remote sensing technology to resource managers in California are highlighted. Applications discussed include the mapping and quantization of wildland fire fuels in Mendocino and Shasta Counties as well as in the Central Valley; the development of a digital spectral/terrain data set for Colusa County; the Forsythe Planning Experiment to maximize the usefulness of inputs from LANDSAT and geographic information systems to county planning in Mendocino County; the development of a digital data bank for Big Basin State Park in Santa Cruz County; the detection of salinity related cotton canopy reflectance differences in the Central Valley; and the surveying of avocado acreage and that of other fruits and nut crops in Southern California. Special studies include the interpretability of high altitude, large format photography of forested areas for coordinated resource planning using U-2 photographs of the NASA Bucks Lake Forestry test site in the Plumas National Forest in the Sierra Nevada Mountains.

Colwell, R. N.↗

NASA NTRS1981

Prime agricultural land monitoring and assessment component of the California Integrated Remote Sensing System

The use of digital LANDSAT techniques for monitoring agricultural land use conversions was studied. Two study areas were investigated: one in Ventura County and the other in Fresno County (California). Ventura test site investigations included the use of three dates of LANDSAT data to improve classification performance beyond that previously obtained using single data techniques. The 9% improvement is considered highly significant. Also developed and demonstrated using Ventura County data is an automated cluster labeling procedure, considered a useful example of vertical data integration. Fresno County results for a single data LANDSAT classification paralleled those found in Ventura, demonstrating that the urban/rural fringe zone of most interest is a difficult environment to classify using LANDSAT data. A general raster to vector conversion program was developed to allow LANDSAT classification products to be transferred to an operational county level geographic information system in Fresno.

Estes, J. E.↗

NASA NTRSDate not supplied

Monitoring and Assessing Heat Vulnerability to Identify Locations for Heat Mitigation Efforts in Sarasota, Florida

Located in the coastal subtropical region, Florida’s Sarasota County receives plenty of sunlight for more than half of the year. However, the ongoing rise in summer temperatures attributed to climate change poses an increasing vulnerability to extreme heat for the residents. Moreover, the area's high relative humidity exacerbates the discomfort of high temperatures, thereby intensifying the severity of heat events and elevating the risks of heat-related illnesses. Our collaborations with Sarasota County Sustainability underscore shared concerns about the impact of urban heat island (UHI) on the community. We utilized Earth observation data from NASA Landsat 8 and Landsat 9’s Thermal Infrared Sensors (TIRS) and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to model UHI effects within the county during the summer from 2019 to 2023. By implementing the open-source Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Cooling software model, ArcGIS ModelBuilder, and principal component analysis, we identified the land surface temperature variance within the county and areas that are least capable of mitigating the effects of UHI. In addition, we use socioeconomic and demographic data as indicators to quantify vulnerability at the census tract level. The results revealed that heat intensity varies significantly across Sarasota County, with the highest temperatures being in the more developed western part of the region. We pinpointed that at least three vulnerable communities reside in high-heat regions: North Sarasota, Venice, and North Port. These areas demonstrate a confluence between socioeconomic sensitivity and environmental hazard, indicating a high priority in future heat mitigation efforts.

Theresia Phoa↗

DOE OSTI2024

Solar PV Water Setbacks: Ordinances (2022) and Extrapolated Trends

This dataset represents solar energy setback requirements from bodies of water based on county ordinances as of April 2022. A setback requirement is a minimum distance from water that an energy project may be developed, and these varied widely across the counties in which they existed. Two versions are provided: one reflecting only the county ordinances and another incorporating extrapolated trends. In the extrapolated version, a default setback of 30 meters was applied in counties without specific water setback regulations. A TIF data file and a PNG map of the data are provided for both versions, showing areas where solar energy is prohibited or permitted across the contiguous United States. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗

DOE OSTI2024

Solar PV Structure Setbacks: Ordinances (2022) and Extrapolated Trends

This dataset represents solar energy setback requirements from structures based on county ordinances as of April 2022. A setback requirement is a minimum distance from a structure that an energy project may be developed, and these varied widely across the counties in which they existed. Two versions are provided: one reflecting only the county ordinances and another incorporating extrapolated trends. In the extrapolated version, a default setback of 61 meters was applied in counties without specific structure setback regulations. A TIF data file and a PNG map of the data are provided for both versions, showing areas where solar energy is prohibited or permitted across the contiguous United States. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗

DOE OSTI2024

Solar PV Road Setbacks: Ordinances (2022) and Extrapolated Trends

This dataset represents solar energy setback requirements from roads based on county ordinances as of April 2022. A setback requirement is a minimum distance from a road that an energy project may be developed, and these varied widely across the counties in which they existed. Two versions are provided: one reflecting only the county ordinances and another incorporating extrapolated trends. In the extrapolated version, a default setback of 30 meters was applied in counties without specific road setback regulations. A TIF data file and a PNG map of the data are provided for both versions, showing areas where solar energy is prohibited or permitted across the contiguous United States. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗

DOE OSTI2024

Wind Turbine Water Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from water based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from water that an energy project may be developed, and these varied widely across the counties in which they existed. Two versions are provided: one reflecting only the county ordinances and another incorporating extrapolated trends. In the extrapolated version, a median setback equivalent to 1.1 times the turbine tip-height was applied in counties that lacked specific water setback regulations. A TIF data file and a PNG map of the data are provided for both versions, showing areas where wind energy is prohibited or permitted across the contiguous United States. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗

DOE OSTI2024

Wind Turbine Transmission Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from transmission based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from transmission infrastructure that an energy project may be developed, and these varied widely across the counties in which they existed. Two versions are provided: one reflecting only the county ordinances and another incorporating extrapolated trends. In the extrapolated version, a median setback equivalent to 1.1 times the turbine tip-height was applied in counties that lacked specific transmission setback regulations. A TIF data file and a PNG map of the data are provided for both versions, showing areas where wind energy is prohibited or permitted across the contiguous United States. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗

DOE OSTI2024

Wind Turbine Structure Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from structures based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from a structure that an energy project may be developed, and these varied widely across the counties in which they existed. Two versions are provided: one reflecting only the county ordinances and another incorporating extrapolated trends. In the extrapolated version, a median setback equivalent to 2 times the turbine tip-height was applied in counties that lacked specific structure setback regulations. A TIF data file and a PNG map of the data are provided for both versions, showing areas where wind energy is prohibited or permitted across the contiguous United States. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗

DOE OSTI2024

Wind Turbine Road Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from roads based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from a road that an energy project may be developed, and these varied widely across the counties in which they existed. Two versions are provided: one reflecting only the county ordinances and another incorporating extrapolated trends. In the extrapolated version, a median setback equivalent to 1.1 times the turbine tip-height was applied in counties that lacked specific railroad setback regulations. A TIF data file and a PNG map of the data are provided for both versions, showing areas where wind energy is prohibited or permitted across the contiguous United States. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗

DOE OSTI2024

Wind Turbine Railroad Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from railroad based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from a railroad that an energy project may be developed, and these varied widely across the counties in which they existed. Two versions are provided: one reflecting only the county ordinances and another incorporating extrapolated trends. In the extrapolated version, a median setback equivalent to 1.1 times the turbine tip-height was applied in counties that lacked specific railroad setback regulations. A TIF data file and a PNG map of the data are provided for both versions, showing areas where wind energy is prohibited or permitted across the contiguous United States. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

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DOE OSTI2023

Long-term carbon intensity reduction potential of K-12 school buildings in the United States

School buildings have a great potential for carbon emission reduction since their annual emission is about 72 million metric tons. Currently, more than 30% of school buildings were built before 1960 and are underperforming. To effectively reduce carbon emissions via school building retrofits, it is critical for policymakers to understand the carbon intensity reduction potential of retrofitting school buildings in different regions. Hence, this study develops a method to comprehensively assess the long-term carbon intensity reduction potential of aggregated commercial buildings on a county-by-county basis in the continental U.S. We apply this method to the K-12 school buildings including primary and secondary school buildings. Here, this paper predicts the carbon intensity reduction potential of K-12 school buildings with eight building retrofit measures from 2022 to 2050 in the continental U.S. The results reveal several interesting findings: (1) In the approximately 3,000 counties of the U.S. from 2022 to 2050, the carbon intensity reduction potential of retrofitting K-12 school buildings in each county ranges from 0.41 kg/m 2 to 40.00 kg/m 2 . (2) Even in the same climate zone, the trends of carbon intensity reduction potential from 2022 to 2050 are different depending on their electricity sources. For example, in a hot and humid climate zone, the carbon intensity reduction potential in Florida will decrease from 2044 to 2048. However, in Mississippi, the carbon intensity reduction potential from 2044 to 2046 will increase due to the termination of the nuclear energy usage. (3) Generally, reducing lighting power density leads to more carbon intensity reduction in most states, but it might not be applicable for states with high clean energy penetration, such as Washington.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗