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All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

An initial analysis of LANDSAT 4 Thematic Mapper data for the classification of agricultural, forested wetland, and urban land covers

An initial analysis of LANDSAT 4 thematic mapper (TM) data for the delineation and classification of agricultural, forested wetland, and urban land covers was conducted. A study area in Poinsett County, Arkansas was used to evaluate a classification of agricultural lands derived from multitemporal LANDSAT multispectral scanner (MSS) data in comparison with a classification of TM data for the same area. Data over Reelfoot Lake in northwestern Tennessee were utilized to evaluate the TM for delineating forested wetland species. A classification of the study area was assessed for accuracy in discriminating five forested wetland categories. Finally, the TM data were used to identify urban features within a small city. A computer generated classification of Union City, Tennessee was analyzed for accuracy in delineating urban land covers. An evaluation of digitally enhanced TM data using principal components analysis to facilitate photointerpretation of urban features was also performed.

Quattrochi, D. A.↗
NASA NTRS1983

Temperatures of shock-induced shear instabilities and their relationship to fusion curves

New emission spectra for MgO and CaAl2Si2O8 (glass) are observed from 430 to 820 nm. Taken with previous data, it is suggested that transparent solids display three regimes of light emission upon shock compression to successively higher pressures: (1) characteristic radiation such as observed in MgO and previously in other minerals, (2) heterogeneous hot spot (greybody) radiation observed in CaAl2Si2O8 and previously in all transparent solids undergoing shock-induced phase transformations, and (3) blackbody emission observed in the high pressure phase regime in NaCl, SiO2, CaO, CaAl2Si2O8, and Mg2SiO4. The onset of the second regime may delineate the onset of shock-induced polymorphism whereas the onset of the third regime delineates the Hugoniot pressure required to achieve local thermal equilibrium in the shocked solid. It is also proposed that the hot spot temperatures and corresponding shock pressures determined in the second regime delineate points on the fusion curves of the high pressure phase.

Schmitt, D. R.↗
NASA NTRS1984

Analysis of synthetic aperture radar data acquired over a variety of land cover

The results of Synthetic Aperture Radar (SAR) measurements over Kershaw County, South Carolina, using HH, HV, and VV polarization and two-incidence angle X-band airborne SAR system and over Baldwin County, Alabama, using HH polarization L-band Shuttle Imaging Radar (SIR-A) are presented. The X-band data indicate higher HH than VV radar return for cypress forest with standing water. Multipolarization (HH, HV, and VV) data help delineate several land-cover types that are difficult to delineate by the single polarization (HH) data. The L-band data indicate that radar return signal strength is highly correlated with tree height or age for three types of pine forest. It is found that delineation of urban/residential from deciduous forest is significantly improved by the inclusion of Landsat multispectral scanner data.

Wu, S.-T.↗
NASA NTRS1986

Use of remotely sensed data for assessing forest stand conditions in the Eastern United States

Techniques for the detection, classification, and measurement of forest disturbances, using digital Landsat data for three study areas (Pennsynvania, North Carolina, and Maine) are reported. Results with respect to (1) the delineation and assessment of forest damage due to the use of two forest insect defoliators, and (2) qualitative assessment of the Multispectral Scanner (MSS) and the Thematic Mapper data for delineating forest stand characteristics are presented. Key results include a development of a statewide MSS digital data base and associated image-processing techniques for accurately delineating insect-damaged and healthy forest areas. For classification of broad land-cover classes which are spectrally homogeneous, the accuracy yielded by the use of either MSS data or TM Simulator data is similar. However, the TMS data provided 20 percent accuracy improvement over the MSS results when detailed (Level III) forest classes were mapped.

Williams, D. L.↗
NASA NTRS1988

Design of the primary pre-TRMM and TRMM ground truth site

The primary objective of the Tropical Rain Measuring Mission (TRMM) were to: integrate the rain gage measurements with radar measurements of rainfall using the KSFC/Patrick digitized radar and associated rainfall network; delineate the major rain bearing systems over Florida using the Weather Service reported radar/rainfall distributions; combine the integrated measurements with the delineated rain bearing systems; use the results of the combined measurements and delineated rain bearing systems to represent patterns of rainfall which actually exist and contribute significantly to the rainfall to test sampling strategies and based on the results of these analyses decide upon the ground truth network; and complete the design begun in Phase 1 of a multi-scale (space and time) surface observing precipitation network centered upon KSFC. Work accomplished and in progress is discussed.

Garstang, Michael↗
NASA NTRS1990

The utilization of satellite observed total ozone to predict tropical cyclone recurvature

The feasibility of using satellite measurements of total ozone to delineate the characteristic upper-tropospheric wave patterns conductive for tropical cyclone recurvature was investigated using measurements by the Nimbus-7 TOMS instrument measurements of total ozone fields were used to delineate the total ozone distribution for the straight-moving, left-curving, and right-curving tropical cyclones. Using these data for 12-h and 24-h forecasts, it is shown that the composite total ozone maps could be used to differentiate the recurving tropical cyclones from nonrecurving systems, suggesting that the majority of the upper-tropospheric waves delineated by total ozone distribution were deep enough to influence the motion of the storms. The left- and the right-recurving tropical cyclones observed during the 12-hr and 24-hr periods had, respectively, higher and lower upper-tropospheric heights downstream than the nonrecurving cyclones.

Rodgers, Edward B.↗
NASA NTRS1994

Cloud properties inferred from 8-12 micron data

A trispectral combination of observations at 8-, 11-, and 12-micron bands is suggested for detecting cloud and cloud properties in the infrared. Atmospheric ice and water vapor absorption peak in opposite halves of the window region so that positive 8-minus-11-micron brightness temperature differences indicate cloud, while near-zero or negative differences indicate clear regions. The absorption coefficient for water increases more between 11 and 12 microns than between 8 and 11 microns, while for ice, the reverse is true. Cloud phases is determined by a scatter diagram of 8-minus-11-micron versus 11-minus-12-micron brightness temperature differences; ice cloud shows a slope greater than 1 and water cloud less than 1. The trispectral brightness temperature method was tested upon high-resolution interferometer data resulting in clear-cloud and cloud-phase delineation. Simulations using differing 8-micron bandwidths revealed no significant degradation of cloud property detection. Thus, the 8-micron bandwidth for future satellites can be selected based on the requirements of other applications, such as surface characterization studies. Application of the technique to current polar-orbiting High-Resolution Infrared Sounder (HIRS)-Advanced Very High Resolution Radiometer (AVHRR) datasets is constrained by the nonuniformity of the cloud scenes sensed within the large HIRS field of view. Analysis of MAS (MODIS Airborne Simulator) high-spatial resolution (500 m) data with all three 8-, 11-, and 12-micron bands revealed sharp delineation of differing cloud and background scenes, from which a simple automated threshold technique was developed. Cloud phase, clear-sky, and qualitative differences in cloud emissivity and cloud height were identified on a case study segment from 24 November 1991, consistent with the scene. More rigorous techniques would allow further cloud parameter clarification. The opportunities for global cloud delineation with the Moderate-Resolution Imaging Spectrometer (MODIS) appear excellent. The spectral selection, the spatial resolution, and the global coverage are all well suited for significant advances.

Strabala, Kathleen I.↗
NASA NTRS2003

Soil Sampling Techniques For Alabama Grain Fields

Characterizing the spatial variability of nutrients facilitates precision soil sampling. Questions exist regarding the best technique for directed soil sampling based on a priori knowledge of soil and crop patterns. The objective of this study was to evaluate zone delineation techniques for Alabama grain fields to determine which method best minimized the soil test variability. Site one (25.8 ha) and site three (20.0 ha) were located in the Tennessee Valley region, and site two (24.2 ha) was located in the Coastal Plain region of Alabama. Tennessee Valley soils ranged from well drained Rhodic and Typic Paleudults to somewhat poorly drained Aquic Paleudults and Fluventic Dystrudepts. Coastal Plain s o i l s ranged from coarse-loamy Rhodic Kandiudults to loamy Arenic Kandiudults. Soils were sampled by grid soil sampling methods (grid sizes of 0.40 ha and 1 ha) consisting of: 1) twenty composited cores collected randomly throughout each grid (grid-cell sampling) and, 2) six composited cores collected randomly from a -3x3 m area at the center of each grid (grid-point sampling). Zones were established from 1) an Order 1 Soil Survey, 2) corn (Zea mays L.) yield maps, and 3) airborne remote sensing images. All soil properties were moderately to strongly spatially dependent as per semivariogram analyses. Differences in grid-point and grid-cell soil test values suggested grid-point sampling does not accurately represent grid values. Zones created by soil survey, yield data, and remote sensing images displayed lower coefficient of variations (8CV) for soil test values than overall field values, suggesting these techniques group soil test variability. However, few differences were observed between the three zone delineation techniques. Results suggest directed sampling using zone delineation techniques outlined in this paper would result in more efficient soil sampling for these Alabama grain fields.

Thompson, A. N.↗
NASA NTRS2021

Wilson Corners SWMU 001 2019-2020 Annual Long-Term Monitoring Report Kennedy Space Center, Florida

This report presents a summary of the long-term monitoring (LTM) activities that occurred in 2019 and 2020 at Wilson Corners, Solid Waste Management Unit 001, at the John F. Kennedy Space Center (KSC), Florida. The site is monitored under KSC’s Resource Conservation and Recovery Act Corrective Action Program. Adaptive site management is being utilized through ongoing assessment, design, and interim measures. This approach also meets the requirements of Chapter 62-780, Florida Administrative Code. The goal of LTM at this site is threefold: to determine groundwater flow characteristics, monitor the downgradient concentration trends, and monitor select locations internal to the groundwater plume. Every 5 years, upgradient and side-gradient monitoring wells are sampled to verify delineation. The last time this was performed was in 2015. Sampling of these wells in 2020 was replaced with the direct push technology investigations in October 2020 and April 2021. The activities presented in this report include three field events: (1) December 2019 -groundwater gauging of 38 monitoring wells and sampling of 36 monitoring wells; (2) May 2020 - groundwater sampling of 7 monitoring wells; and (3) December 2020 - groundwater gauging of 49 monitoring wells and sampling of 43 monitoring wells. During the December 2019 and May 2020 events, monitoring wells were sampled using passive diffusion bags and were analyzed for a “full list” of volatile organic compounds (VOCs), including Freon 113. During the December 2020 event, the low flow sampling method was used, and samples were analyzed for a “select list” of VOCs, including Freon 113. The following conclusions can be made based on the 2019 and 2020 LTM results: •In December 2019 and December 2020, groundwater flow for the site was generally to the west with the individual zones only varying by occasional northerly and southerly components. This is generally consistent with historical observations at the site. •The GCTL plume continues to extend both horizontally and vertically beyond our current monitoring well network. •The vertical extent of VOCs was historically generally delineated by monitoring wells screened greater than 48 feet bls. The results from the two vertical extent monitoring wells WILC-MW0078 and WILC-MW0130 that were sampled during the 2019 and 2020 LTM indicate that groundwater VOC concentrations in both wells were greater than the GCTL. •Freon 113 was not detected above GCTLs during the 2019 and 2020 LTM events. Based on groundwater sampling activities performed during this reporting period, including recent DPT groundwater sampling conducted for the implementation of an air sparge system, the following recommendations are provided: •Install 10 new monitoring wells, which will be sampled along with 49 existing monitoring wells, to assist with delineation of the low concentration plume. The wells are listed inTable 4-1, and the proposed locations are presented on Figures4 -1 through 4-5. (Figures 4-1, 4-2, 4-3, and 4-5 also show updated plumes and proposed performance monitoring well locations. This information will be discussed and presented under a separate cover.) •Modify the annual LTM sampling plan as presented inTable 4-1. •Sampling for future events at the site will be conducted using low flow pumping methods. The next annual LTM sampling event is currently planned for December 2021. Please note the 10 new monitoring wells will not be installed before this event but will be installed as part of the upcoming IM construction and will be sampled during baseline sampling, along with the 49 existing monitoring wells. Following this sampling event, it is recommended that the Annual LTM be combined with the performance monitoring under the IM implementation, and LTM be temporarily discontinued. Objectives of the 2021 LTM are to: (i) evaluate groundwater gradient and flow direction by collecting depth to water measurements from LTM wells; (ii) continue monitoring the peripheral VOC trends in the northern, southern, and western portions of the site by monitoring existing wells and installing and monitoring new wells as recommended; and (iii) monitor select internal plume wells.

Jennifer Lynn Joyal↗
NASA NTRS2022

Wilson Corners Solid Waste Management Unit (SWMU) 001: 2021 Annual Long-Term Monitoring Report, Kennedy Space Center, Florida

This report presents a summary of the long-term monitoring (LTM) activities that occurred in 2021 at Wilson Corners, Solid Waste Management Unit (SWMU) 001, at Kennedy Space Center (KSC), Florida. The site is monitored under KSC’s Resource Conservation and Recovery Act (RCRA) Corrective Action Program. Adaptive site management is being utilized through ongoing assessment, design, and interim measures (IM). Annual LTM of the groundwater is also being conducted at the site. This approach also meets the requirements of Chapter 62-780, Florida Administrative Code (F.A.C.). The goal of LTM at this site is threefold: to determine groundwater flow characteristics, monitor the downgradient concentration trends, and monitor select locations internal to the groundwater plume. Every 5 years, upgradient and side-gradient monitoring wells are sampled to verify delineation. The last time this was performed was in 2015. The sampling of these wells in 2020 was replaced with the direct push technology (DPT) investigations completed in October 2020 and April 2021. This DPT groundwater data was presented in an Advance Data Package (ADP) in September 2021 and discussed in the Implementation Work Plan (IWP) dated November 2021 for installation of an air sparge (AS) system. Based on results from groundwater sampling activities performed during the previous reporting period, including the 2020 and 2021 DPT groundwater sampling, it was determined that the LTM sampling plan was no longer meeting the goal of LTM because delineation was not verified. The 2021 LTM sampling plan was modified to include the sampling of monitoring wells located around the perimeter of the low concentration plume (LCP); the area with concentrations of contaminants of concern [COCs] greater than Groundwater Cleanup Target Levels [GCTLs]), and sampling of 10 monitoring wells proposed for installation (April 2021 KSC Remediation Team (KSCRT) Meeting, Decision 2104-D32). The modified LTM plan received team consensus at the September 2021 KSCRT Meeting (Decision Number 2109-D03), and sampling of the existing monitoring wells was completed in December 2021. The proposed monitoring wells are planned for installation in late 2022, concurrent with ongoing IM construction activities. December 2021 LTM data was presented at the May 2022 KSCRT Meeting, and activities are summarized in this report. The activities presented in this report include the December 2021 groundwater gauging of 42 monitoring wells and sampling of 44 monitoring wells. During the December 2021 event, the low flow sampling method was used, and samples were analyzed for a select list of volatile organic compounds (VOCs), including 1,1,2-trichloro-1,2,2-trifluoroethane (Freon 113). The following conclusions can be made based on the 2021 LTM results: - In December 2021, groundwater flow for the site was generally to the west at all intervals. This is generally consistent with historical observations at the site, with the exception of a southwest and southeast flow component observed at 34 to 48 feet below land surface (bls). - The vertical extent of VOCs was historically delineated by monitoring wells screened greater than 48 feet bls. The results from the two vertical extent monitoring wells, WILC-MW0078 (screened 65 to 70 feet bls) and WILC-MW0130 (screened 56 to 66 feet bls) that were sampled during the 2021 LTM indicate that groundwater vinyl chloride (VC) concentrations in both wells were greater than the GCTL. The Remediation Team has previously agreed to delay deeper DPT investigations in this area to prevent the creation of additional pathways for vertical migration. - The LCP continues to extend both horizontally, predominantly to the west, and vertically beyond the current monitoring well network, with some retraction observed to the southeast. Evaluation of this data combined with data from the 2020 and 2021 DPT sampling event indicate that the LCP encompasses an estimated 20.7 acres based on an expanded sampling area, as compared to the 2020 LCP footprint of 17.0 acres. - Freon 113 was not detected above GCTLs during the 2021 LTM event. Based on groundwater sampling activities performed in 2021, including April 2021 DPT groundwater sampling, the following recommendations are provided: - Perform the next LTM sampling event, targeted to occur in 2023, concurrently with the IM baseline sampling prior to AS system installation; - Include sampling from nine monitoring wells that are planned to be installed in late 2022, concurrent with upcoming IM construction activities. Installation of one deep vertical well, screened 70 to 80 feet bls, will be delayed to prevent the creation of an additional pathway for vertical migration; - Continue to sample under the modified annual LTM plan as presented in Table 4-1 concurrently with IM baseline sampling; and - Once the AS system install and start-up is complete, select monitoring wells from the LTM program will transition into the performance monitoring plan, and LTM will be temporarily discontinued. Performance monitoring will be performed quarterly, and the monitoring well network will be evaluated following the first performance monitoring sampling event.

long-term monitoring (LTM)↗
NASA NTRS2024

Hydrocarbon Burn Facility, SWMU 007 Per- and Polyfluoroalkyl Substances (PFAS) Assessment Report Addendum

This document discusses the Per-and Polyfluoroalkyl Substances (PFAS) assessment activities performed from May through August 2023 at the Hydrocarbon Burn Facility (HBF) located at Kennedy Space Center (KSC), Florida. HBF was used for firefighting training between 1966 and 1994. Aqueous film-forming foams (AFFFs) that contained PFAS were used as suppressants for fighting petroleum fuel fires during training. PFAS sampling was first completed at HBF in 2015. This PFAS Assessment Report Addendum (ARA) is a continuation of sampling efforts, with an overall objective to further delineate PFAS concentrations in groundwater to the pGCTLs and the United States Environmental Protection Agency (EPA) Tapwater Regional Screening Levels (RSLs) dated November 2023 and better understand groundwater to surface water interaction at the Site. The field activities presented in this PFAS ARA were conducted between May and August 2023 and included the collection of 132 direct push groundwater samples and the collection of five colocated surface water, sediment, and pore water samples from locations south/southeast of HBF in August 2023. Exceedances of the pGCTLs and Tapwater RSLs were observed in the direct push groundwater results; however, groundwater has been delineated to the pGCTLs. Exceedances of the Florida provisional Surface Water Screening Levels (pSWSLs) were observed in surface water and porewater, and concentrations of PFAS in these media confirm PFAS migration within surface channels to the south of the HBF site area. Maximum sediment concentrations, which correlate with the maximum surface water and porewater concentrations, demonstrate that PFAS impacted surface water is the source of sediment impacts. Overall, elevated concentrations of PFAS are centered on the HBF site area that trend north and south along the surface water filled swales and along the edge of Banana River. Based on analytical results, not all surface water features in this area exhibit evidence of transport. PFAS migration/transport appears to be more dominant in surface water features during the wet season. Discharges to the Banana River primarily occur where surface water facilitates transport. In contrast, groundwater transport is more effective during the dry season. During precipitation events in either the dry season or the wet season, there appears to be migration from the intermediate groundwater zone to the shallow zone into the surface water features. Additional sampling and data collection is recommended to support further refinement of PFAS groundwater delineation, a remedial alternative evaluation, and the fate and transport model.

Jennifer Buel↗
DOE OSTI2020

GIS-Based Modeling of Contaminated Soil Volumes at Multiple Sites in the Formerly Utilized Sites Remedial Action Program - 20149

The remediation of hazardous, toxic, and radioactive waste (HTRW) sites produces cost-related risks associated with the estimation of contaminated soil or debris volumes. Historical risk-management techniques include cost contingencies to cover volume uncertainties that affect project budgeting and decision-making. The Buffalo District teamed with project partners to lessen volume uncertainty and reduce project risks at multiple HTRW sites managed under the Formerly Utilized Sites Remedial Action Program (FUSRAP). Historical remedial investigations under FUSRAP commonly identified the presence of radiological material in site media, the associated human health risk, and then areas of remediation. To manage remedial execution and reduce risk, pre-design or remediation-phase sampling essentially 'chased' contamination, which was not conducive to efficient predictive budgeting derived from Feasibility Study (FS) cost analyses. The Buffalo District first optimized their approach to better understand volume uncertainty by utilizing the Argonne National Laboratory's Bayesian Approaches for Adaptive Spatial Sampling (BAASS) software [1]. BAASS processed soft data (e.g., gamma walk-over data) and spatial sampling data to estimate the lateral extent of contaminated soil irrespective of depth (i.e., gross contamination extent) and define areas of contaminant uncertainty. The software performed a binary transformation of contaminant concentrations at all sampling points based upon remedial action goals or a sum of ratios approach (i.e., clean, impacted, or range of impacts in soil). The model produced two-dimensional (horizontal) contaminant probability contours and statistical uncertainty in the sampling coverage and resulting contaminant extents. This method was translated vertically by partitioning the sampling data into depth brackets that produced a stacked representation of contaminant extents and uncertainty in the subsurface (i.e., similar to construction lifts). The results commonly led to a better understanding of project uncertainty and the need for sampling strategies that produce high-confidence soil volumes, which control costs. The BAASS-based delineations were eventually replaced by Empirical Bayesian Kriging (EBK) methods available in ArcGIS Spatial or 3D Analysts [2]. The EBK method calculates contaminant probability zones derived from user-controlled semivariograms of the spatial datasets. The resulting probability zones (e.g., 50% or 80% of contaminant probability) represent the two-dimensional surface delineation of the overall horizontal remedial area, similarly to BAASS. However, unlike BAASS, the vertical sampling data within these probability zones became vertical control points to contour a subterranean surface that connects subsurface points to the land-surface delineations of contamination. The resulting representation of horizontal and vertical impacts within an enclosed envelop (volume) of soil included uncertainty distributions that are used to plan uncertainty-reduction sampling. These data-driven and math-based models of three-dimensional sampling results produced well-bounded remedial volumes for project planning and better uncertainty predictions during project budgeting. The EBK method was applied to several FUSRAP sites managed by the Buffalo District and compared to less rigorously modeled sites previously remediated by the District. The comparison of modeled to actual remediated volumes provide a basis for validating the volume-estimation method. This comparison is important to ensure modeled volumes match physical boundaries of site remediation. FUSRAP sites with denser investigative sampling and lesser volume uncertainty proved useful in remedial planning and contracting. The Buffalo District noted that historical sites with sparser sampling arrays had greater disparity between estimated volumes and final remedial volumes. The benefit achieved over the cost of detailed soil sampling appears positive for FUSRAP projects, especially where impacts vary widely and appear unbounded by investigation-phase sampling. The subsequent Empirical Bayesian Kriging of contamination coupled with vertical contouring for soil estimations reduces uncertainty in soil volumes or indicates where sampling is required to reduce uncertainty, which together optimize remedial planning and budgeting. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Human–mouse comparison of the multistage nature of radiation carcinogenesis in a mathematical model

Abstract Mouse models are vital for assessing risk from environmental carcinogens, including ionizing radiation, yet the interspecies difference in the dose response precludes direct application of experimental evidence to humans. Herein, we take a mathematical approach to delineate the mechanism underlying the human–mouse difference in radiation‐related cancer risk. We used a multistage carcinogenesis model assuming a mutational action of radiation to analyze previous data on cancer mortality in the Japanese atomic bomb survivors and in lifespan mouse experiments. Theoretically, the model predicted that exposure will chronologically shift the age‐related increase in cancer risk forward by a period corresponding to the time in which the spontaneous mutational process generates the same mutational burden as that the exposure generates. This model appropriately fitted both human and mouse data and suggested a linear dose response for the time shift. The effect per dose decreased with increasing age at exposure similarly between humans and mice on a per‐lifespan basis (0.72‐ and 0.71‐fold, respectively, for every tenth lifetime). The time shift per dose was larger by two orders of magnitude in humans (7.8 and 0.046 years per Gy for humans and mice, respectively, when exposed at ~35% of their lifetime). The difference was mostly explained by the two orders of magnitude difference in spontaneous somatic mutation rates between the species plus the species‐independent radiation‐induced mutation rate. Thus, the findings delineate the mechanism underlying the interspecies difference in radiation‐associated cancer mortality and may lead to the use of experimental evidence for risk prediction in humans.

Oncology↗
DOE OSTI2025

Application of Atmospheric Gases and Particulate Matter to the Assessment of Urban Heat Island

Background: Urban heat island (UHI), where built areas are warmer compared to non-urban regions, increases human related diseases and mortality. A key challenge in UHI analysis is the designation of sites as urban or suburban/rural; however, the growing complexity of green spaces in urban areas and the predominance of the transportation sector in nonurban areas creates a dilemma for distinct delineation. Objectives: This study aims to utilize the variability of atmospheric components such as particulate matter (PM), inorganic gases, and volatile organic compounds (VOCs) as direct tracers of the degree of urbanization for ground-based measurements to fully comprehend UHI in convoluted regions with indistinct delineation of urban and nonurban environments. Methods: Atmospheric gases and aerosols were used as direct tracers of urbanization for UHI analysis. Inorganic gases and particulate matter were monitored in two sites in a southeastern US city with varying degrees of urbanization. VOCs were analyzed using a proton transfer reaction time-of-flight mass spectrometer. Results: The more-urbanized site exhibited warmer night conditions and elevated total oxidant levels, leading to the formation of nanometer-sized particles. Machine learning analysis revealed similar atmospheric pollutant profiles for both sites, suggesting comparable sources and variability. Biogenic VOCs were enhanced at the less-urbanized site; however, levels of anthropogenic aromatic VOCs were comparable for both sites. A comprehensive mass spectra analysis revealed distinct molecular backbones per site that further affirmed the applicability of VOCs as indicators of urbanization. Conclusion: This study concludes that VOCs provide more direct and accurate information than typical inorganic gases and PM parameters for characterizing the degree of urbanization. Further exploration of VOCs can enhance our understanding of UHI dynamics and its interaction with vegetation in urban green spaces.

Air quality sensor↗
DOE OSTI2025

Seismicity-constrained fault detection and characterization with a multitask machine learning model

Geological fault detection and characterization are crucial for understanding subsurface dynamics across scales. While methods for fault delineation based on either seismicity location analysis or seismic image reflector discontinuity are well-established, a systematic approach that integrates both data types remains absent. We develop a novel machine learning model that unifies seismic reflector images and seismicity location information to automatically identify geological faults and characterize their geometrical properties. The model encodes a seismic image and a seismicity location image separately, and fuses the encoded features with a spatial-channel attention fusion module to improve the learning of important features in both inputs. We design an automated strategy to generate high-quality synthetic training data and labels. To improve the realism of the seismicity location image, we include random seismicity noise and missing seismicity location associated with some of the faults. We validate the model’s efficacy and accuracy using synthetic data examples and two field data examples. Moreover, we show that fine-tuning the trained model with a small, domain-specific dataset enhances its fidelity for field data applications. The results demonstrate that integrating seismicity location and seismic images into a unified framework allows the end-to-end neural network to achieve higher fidelity and accuracy in delineating subsurface faults and their geometrical properties compared with image-only fault detection methods. Our approach offers an adaptive data-driven tool for geological fault characterization and seismic hazard mitigation, bridging the gap between seismicity location and image-based fault detection methods.

58 GEOSCIENCES↗
DOE OSTI2020

Probabilistic risk-based Area of Review (AoR) determination for a deep-saline carbon storage site

Regulatory oversight of a geologic carbon sequestration (GCS) project relies on iterative estimations, throughout the project lifetime, of the area where increased risks to underground sources of drinking water (USDWs) may occur due to injection of CO2. This area, referred to as Area of Review (AoR), is typically delineated by predicting the migration of fluid between the reservoir and the lowermost USDW via an open wellbore using predictions from physics-based reservoir simulators. The inherent uncertainty in input parameters used in reservoir modeling therefore affects the accuracy of determining the AoR for a project. Furthermore, the standard analytical approaches for calculating a critical pressure to delineate the risk area yield an infinite AoR for cases where the injection reservoir is overpressured relative to the USDW. A methodology is presented in this paper to better characterize the risk to USDWs while accounting for the uncertainty in reservoir modeling, with an application to a permitted GCS project with an overpressured injection formation, FutureGen 2.0. The methodology is demonstrated using the National Risk Assessment Partnership’s open-source integrated assessment model (NRAP-Open-IAM) to develop a probabilistic estimate of impact risk to USDW quality. CO2 and pressure predictions from the reservoir modeling conducted using the STOMP-CO2 simulator for the FutureGen 2.0 site are used in a NRAP-Open-IAM model with reservoir, wellbore, and aquifer components to: (1) assess the extent of potential leakage into the USDW for the predicted reservoir pressure conditions; (2) evaluate the extent of potential impact using “no-net-degradation” thresholds; and (3) account for uncertainty in reservoir permeabilities.

03 NATURAL GAS↗
DOE OSTI2026

Rapid Coal-Ash Characterization using Geophysical Methods & Machine Learning

Coal combustion products (CCP) are challenging to delineate in heterogeneous field settings. Conventional methods (test pits, coring, and laboratory analyses) are labor-intensive, slow, invasive, and provide sparse spatial coverage. This study evaluates whether rapid non-invasive geophysical screening methods—induced polarization (IP), magnetic susceptibility, and nuclear magnetic resonance (NMR) —combined with surface colorimetry (RGB_24), can discriminate CCP-soil mixtures and provide reliable estimates of CCP content. Laboratory measurements were collected on five CCP-soil mixtures (series) and modeled using (i) a linear baseline, (ii) a calibrated non-linear (power-mean) model, and (iii) a machine-learning (ML) Random Forest approach, with validation via leave-one-series-out and site-specific tests. Across the five series, individual signals—particularly IP and magnetic susceptibility—were strongly predictive of ash content but were consistently outperformed by combined models. The pooled calibrated non-linear and ML models captured the observed non-linearity and achieved high accuracy and precision, improving on linear fits. Colorimetry showed the weakest direct relationship with ash content for the tested samples but improved performance when included in multi-signal models. At pre-selected 3.5% decision threshold, calibrated and ML approaches yielded near-perfect classification (Matthews correlation coefficient ˜ 1), suggesting strong practical operability for field screening. Additionally, field-analog tests highlighted the role of endmembers—accuracy declined without access to end-member measurements but was largely recovered by collecting a minimal labeled pair for local recalibration. With end members, accuracy remained high. Globally trained models performed well on three operational unknowns; however, series-specific refits provided the most accurate predictions. Overall, these results highlight the potential of combining rapid geophysics and minimal local calibration for improved coal-ash delineation.

Peshtani, Klaudio↗
DOE OSTI2023

Influence of urban extent discrepancy on the estimation of surface urban heat island intensity: A global-scale assessment in 892 cities

The estimation of surface urban heat island intensity (SUHII) is crucial for studying the urban thermal environment, which is influenced not only by the commonly known definition of rural reference but also by the delineation of urban extent. Existing studies relies on various urban extent products defined in different ways, and the influence of urban extent discrepancy (UED) on SUHII estimates still remains unclear. In this study, we collected five open-source global urban extent products (GUEPs) for the year 2015 and corresponding daily land surface temperature (LST) observations (MYD11A1). Based on these products, we quantified the UED-induced uncertainty in SUHII estimates by comparing absolute difference (ΔSUHII AD ) and relative difference (ΔSUHII RD ) in SUHII among GUEPs across 892 global cities. Additionally, we introduced an ISF-constrained (ISF–C) method to reduce SUHII differences among GUEPs by constraining the impervious surface fraction (ISF) within urban and rural extents. The results show that urban extents delineated by different GUEPs are not consistent, leading to their difference in ISF as well as LST, which in turn causes uncertainties in the estimated SUHII. On average for global cities, the annual daytime and nighttime ΔSUHII AD are 0.46 ± 0.02 °C (mean ± 95% confidence interval) and 0.24 ± 0.01 °C, with corresponding ΔSUHII RD of 42.0 ± 2.7% and 35.2 ± 2.3%, respectively. The UED-induced uncertainty in SUHII estimates varies among climate zones, and the annual daytime ΔSUHII RD averaged for cities located in the arid zone reaches up to 60.8 ± 6.6%, which is nearly twice as high as that in other climate zones. More importantly, both ΔSUHII AD and ΔSUHII RD show lower values when using the ISF-C method, implying the effectiveness of this method. This study highlights the non-negligible impact of UED on the estimation of SUHII, which requires more attention due to the inconsistency of urban extents among current products.

54 ENVIRONMENTAL SCIENCES↗