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DOE OSTI2025

SPRUCE: Shrub-Layer Vegetation Biomass Collection Metadata, Marcell Experimental Forest, Minnesota, August 2025

This data set contains metadata associated with shrub-layer vegetation samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2025. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored in the SPRUCE archive and may be available for further analysis by request. See below under 7 Sample Access. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B069L. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR.

Birkebak, Joshua [ORNL] (ORCID:0009000955611494)↗

DOE OSTI2018

REE and Coal Open Geodatabase Collection

The REE and Coal Open Database is an online collection of subsurface contextual data from publicly available geological, geochemical, and geospatial resources. These data align to and support execution of NETL’s REE coal assessment method. The database includes basin- and national-level spatial datasets, in addition to other non-spatial data that support the assessment approach. Data in this collection are sourced from a range of authoritative, public sources, including NETL, U.S. Geological Survey (USGS), Energy Information Administration (EIA), and state geological surveys.

coal↗

DOE OSTI2024

RokBase Core Facility Data Collection

The RokBase Core Facility Data Collection v1.0 is an aggregation of information on the locations and collections of geologic core facilities in the United States. It contains two spatial files, their corresponding attribute tables within a catalog, and an interactive web map and dashboard. It is intended to be used for research and comparison purposes, see full disclaimer and credits. Please contact NETL if revisions / corrections can be made to improve this dataset.

core facility location↗

DOE OSTI2017

FOKKER-PLANCK ANALYSIS OF TRANSVERSE COLLECTIVE INSTABILITIES IN ELECTRON STORAGE RINGS

We analyze single bunch transverse instabilities due to wakefields using a Fokker-Planck model. We expand on the work of Suzuki [1], writing out the linear matrix equation including chromaticity, both dipolar and quadrupolar transverse wakefields, and the effects of damping and diffusion due to the synchrotron radiation. The eigenvalues and eigenvectors determine the collective stability of the beam, and we show that the predicted threshold current for transverse instability and the profile of the unstable agree well with tracking simulations. In particular, we find that predicting collective stability for high energy electron beams at moderate to large values of chromaticity requires the full Fokker-Planck analysis to properly account for the effects of damping and diffusion due to synchrotron radiation.

FOKKER-PLANCK ANALYSIS↗

DOE OSTI2017

COLLECTIVE EFFECTS AT INJECTION FOR THE APS-U MBA LATTICE

The Advanced Photon Source has proposed an upgrade to a multi-bend achromat (MBA) with a proposed timing mode calls for 48 bunches of 15 nC each. In this mode of operation we find that phase space mismatch from the booster can drive large wakefields that in turn may limit the current below that of the nominal collective instability threshold. We show that collective effects at injection lead to emittance growth that makes usual off-axis accumulation very challenging. On-axis injection ameliorates many of these issues, but we find that transverse feedback is still required. We explore the role of impedance, feedback, and phase-space mismatch on transverse instabilities at injection.

APS-U MBA LATTICE↗

DOE OSTI2017

PANSOPHY, a JLAB SRF engineering data management system, supporting data collection, retrieval and analysis utilized by LCLS-II

Pansophy is an Engineering Data Management System that provides a comprehensive solution for managing information in the production and testing of cryomodules. It is especially suited to supporting the Data & Quality Management Systems for large projects like LCLS-II. With extensive amounts of data collected for an individual project, data retrieval to facilitate feedback and enhancement of production and processing activities is a high priority. The priority shares importance with the needs of managing the project, including production status, NCR, and Quality Management reports. Recent Pansophy enhancements have been to Data and Quality management reports and statistical analysis. Such enhancements include a database driven menu system, extended MSWord macro and preprocessing of travelers, and an extensive reporting system. The reporting system allows managers and group leaders to quickly respond to the needs of the project in areas of cavity and cryomodule production, data collection, NCR, Quality Management and schedule. Extensions include integration with the SRF inventory system PRIMeS, allowing traceability from receiving of manufactured parts to final cryomodule product.

Bookwalter, Valerie D.↗

DOE OSTI2013

Variation in Uranium Isotopic Ratios 238 U/ 235 U and 234 U/ 238 U and 236 U/ 238 U in Water Samples Collected from Private Wells in the Española Basin, Santa Fe, New Mexico

This report presents uranium concentration and variation in uranium isotopic ratios 238 U/ 235 U and 234 U/ 238 U and 236 U/ 238 U in water samples collected from private wells in the Española basin in New Mexico. The document focuses specifically on analyzing variations in the uranium isotopic composition of the different water samples. The data presented in this report were obtained from water samples collected during the fall of 2012. A list of the different sampling locations as identified by their GPS coordinates is presented in Table 1 and represented on a map shown in Figure 1. Water temperature, conductivity, pH, and redox conditions (ORP) were also measured at the time of sampling and are also presented in Table 1. The pH of the samples ranged between 7.10 and 8.49, the temperature between 11.30 and 16.58 ˚C, and the ORP between -182 and 202 mV. The conductivity of the samples was between 454 µS·cm -1 and 1066 µS·cm -1 . The concentration of uranium in the samples varied widely and ranged between 11.5 and 776 µg/L. Uranium isotopic ratios conducted by Thermal Ionization Mass Spectrometry (TIMS) showed natural 238 U/ 235 U within analytical uncertainty. The water samples showed some variations in the isotopic ratios of 234 U/ 238 U, varying from atom ratios of 54.9×10 -6 to 226×10 -6 (activity ratios of 1.00 to 4.11), and indicating enrichment of 234 U in many of the water samples. These isotopic ratios are within the range observed in natural water. Such enrichments in 234 U in natural waters are common and typically attributed to natural processes. There was no detectable 236 U in any of the samples analyzed.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2013

COMPARISON OF RESULTS FOR QUARTER 4 SURFACE WATER SPLIT SAMPLES COLLECTED AT THE NUCLEAR FUELS SERVICES SITE, ERWIN, TN

Oak Ridge Associated Universities (ORAU), under the Oak Ridge Institute for Science and Education (ORISE) contract, collected split surface water samples with Nuclear Fuel Services (NFS) representatives on June 12, 2013. Representatives from the U.S. Nuclear Regulatory Commission (NRC) and the Tennessee Department of Environment and Conservation were also in attendance. Samples were collected at four surface water stations, as required in the approved Request for Technical Assistance number 11-018. These stations included Nolichucky River upstream (NRU), Nolichucky River downstream (NRD), Martin Creek upstream (MCU), and Martin Creek downstream (MCD). Both ORAU and NFS performed gross alpha and gross beta analyses, and Table 1 presents the comparison of results using the duplicate error ratio (DER), also known as the normalized absolute difference. A DER ≤ 3 indicates at a 99% confidence interval that split sample results do not differ significantly when compared to their respective one standard deviation (sigma) uncertainty (ANSI N42.22). The NFS split sample report specifies 95% confidence level of reported uncertainties (NFS 2013). Therefore, standard two sigma reporting values were divided by 1.96. In conclusion, most DER values were less than 3 and results are consistent with low (e.g., background) concentrations. The gross beta result for sample 5198W0014 was the exception. The ORAU gross beta result of 6.30 &plusmn 0.65 pCi/L from location NRD is well above NFS's non-detected result of 1.56 &plusmn 0.59 pCi/L. NFS's data package includes no detected result for any radionuclide at location NRD. At NRC's request, ORAU performed gamma spectroscopic analysis of sample 5198W0014 to identify analytes contributing to the relatively elevated gross beta results. This analysis identified detected amounts of naturally-occurring constituents, most notably Ac-228 from the thorium decay series, and does not suggest the presence of site-related contamination.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

COMPARISON OF RESULTS FOR QUARTER 3 SURFACE WATER SPLIT SAMPLES COLLECTED AT THE NUCLEAR FUEL SERVICES SITE, ERWIN, TENNESSEE

Oak Ridge Associated Universities (ORAU), under the Oak Ridge Institute for Science and Education (ORISE) contract, collected split surface water samples with Nuclear Fuel Services (NFS) representatives on March 20, 2013. Representatives from the U.S. Nuclear Regulatory Commission and the Tennessee Department of Environment and Conservation were also in attendance. Samples were collected at four surface water stations, as required in the approved Request for Technical Assistance number 11-018. These stations included Nolichucky River upstream (NRU), Nolichucky River downstream (NRD), Martin Creek upstream (MCU), and Martin Creek downstream (MCD). Both ORAU and NFS performed gross alpha and gross beta analyses, and Table 1 presents the comparison of results using the duplicate error ratio (DER), also known as the normalized absolute difference. A DER {<=} 3 indicates that at a 99% confidence interval, split sample results do not differ significantly when compared to their respective one standard deviation (sigma) uncertainty (ANSI N42.22). The NFS split sample report does not specify the confidence level of reported uncertainties (NFS 2013). Therefore, standard two sigma reporting is assumed and uncertainty values were divided by 1.96. In conclusion, most DER values were less than 3 and results are consistent with low (e.g., background) concentrations. The gross beta result for sample 5198W0012 was the exception. The ORAU result of 9.23 &plusmn 0.73 pCi/L from location MCD is well above NFS's result of -0.567 &plusmn 0.63 pCi/L (non-detected). NFS's data package included a detected result for U-233/234, but no other uranium or plutonium detection, and nothing that would suggest the presence of beta-emitting radionuclides. The ORAU laboratory reanalyzed sample 5198W0012 using the remaining portion of the sample volume and a result of 11.3 &plusmn 1.1 pCi/L was determined. As directed, the laboratory also counted the filtrate using gamma spectrometry analysis and identified only naturally occurring or ubiquitous man-made constituents, including beta emitters that are presumably responsible for the elevated gross beta values.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Comparison of results for quarter 5 surface water split samples collected at the nuclear fuel services site Erwin Tennessee

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

The Transportation Leapfrog: Using Smart Phones to Collect Driving Data and Model Fuel Economy in India

Car ownership in India is expected to skyrocket in the coming decades, strongly driven by rising incomes. This phenomenon provides unprecedented opportunities for automakers and equally unprecedented social and environmental challenges. Policymakers, urban planners and civil society see this car boom leading to an explosion in problems related to congestion, infrastructure, air pollution, safety, higher oil imports and climate change. For all these stakeholders to take effective action, good data on how people use their cars, their demand for mobility and their behavior in mobility is essential. Unfortunately, there is very little data on the Indian transport sector as a whole and virtually none on real-world vehicle performance and use. The rapid development of high quality mobile telecommunications infrastructure provides India with the opportunity to leapfrog the West in cheaply collecting vast amounts of useful data from transportation. In this paper, we describe a pilot project in which we use commercial smart phone apps to collect per second car driving data from the city of Pune, instantly upload it through 3G and prepare it for analysis using advanced noise filtering algorithms for less than $1 per day per car. We then use our data in an Autonomie simulation to show that India’s currently planned fuel economy test procedures will result in over-estimates of fuel economy of approximately 35% for a typical Indian car when it is operated in real world conditions. Supporting better driving cycle development is just one of many applications for smart phone derived data in Indian transportation.

25 ENERGY STORAGE↗

DOE OSTI2015

Analysis of Dust Samples Collected from an Unused Spent Nuclear Fuel Interim Storage Container at Hope Creek, Delaware

In July, 2014, the Electric Power Research Institute and industry partners sampled dust on the surface of an unused canister that had been stored in an overpack at the Hope Creek Nuclear Generating Station for approximately one year. The foreign material exclusion (FME) cover that had been on the top of the canister during storage, and a second recently-removed FME cover, were also sampled. This report summarizes the results of analyses of dust samples collected from the unused Hope Creek canister and the FME covers. Both wet and dry samples of the dust/salts were collected, using SaltSmart(TM) sensors and Scotch-Brite(TM) abrasive pads, respectively. The SaltSmart(TM) samples were leached and the leachate analyzed chemically to determine the composition and surface load per unit area of soluble salts present on the canister surface. The dry pad samples were analyzed by X-ray fluorescence and by scanning electron microscopy to determine dust texture and mineralogy; and by leaching and chemical analysis to deter mine soluble salt compositions. The analyses showed that the dominant particles on the canister surface were stainless steel particles, generated during manufacturing of the canister. Sparse environmentally - derived silicates and aluminosilicates were also present. Salt phases were sparse, and consisted of mostly of sulfates with rare nitrates and chlorides. On the FME covers, the dusts were mostly silicates/aluminosilicates; the soluble salts were consistent with those on the canister surface, and were dominantly sulfates. It should be noted that the FME covers were w ashed by rain prior to sampling, which had an unknown effect of the measured salt loads and compositions. Sulfate salts dominated the assemblages on the canister and FME surfaces, and included Ca-SO 4 , but also Na-SO 4 , K-SO 4 , and Na-Al-SO 4 . It is likely that these salts were formed by particle - gas conversion reactions, either prior to, or after, deposition. These reactions involve reaction of carbonate, chloride, or nitrate salts with at mospheric SO 2 , sulfuric acid, or a mmonium sulfate to form sulfate minerals. The Na-Al-SO 4 phase is unusual, and may have formed by reaction of Na-Al containing phases in aluminum smelter emissions with SO 2 , also present in smelter emissions. An aluminum smelter is located in Camden, NJ, 40 miles NE of the Hope Creek Site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Value Stream Mapping: Foam Collection and Processing

The effort to collect and process foam for the purpose of recycling performed by the Material Sustainability and Pollution Prevention (MSP2) team at Sandia National Laboratories is an incredible one, but in order to make it run more efficiently it needed some tweaking. This project started in June of 2015. We used the Value Stream Mapping process to allow us to look at the current state of the foam collection and processing operation. We then thought of all the possible ways the process could be improved. Soon after that we discussed which of the "dreams" were feasible. And finally, we assigned action items to members of the team so as to ensure that the improvements actually occur. These improvements will then, due to varying factors, continue to occur over the next couple years.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Handbook: Collecting Groundwater Samples from Monitoring Wells in Frenchman Flat, CAU 98

Frenchman Flat basin on the Nevada National Security Site (NNSS) contains Corrective Action Unit (CAU) 98, which is comprised of ten underground nuclear test locations. Environmental management of these test locations is part of the Underground Test Area (UGTA) Activity conducted by the U.S. Department of Energy (DOE) under the Federal Facility Agreement and Consent Order (FFACO) (1996, as amended) with the U.S. Department of Defense (DOD) and the State of Nevada. A Corrective Action Decision Document (CADD)/Corrective Action Plan (CAP) has been approved for CAU 98 (DOE, 2011). The CADD/CAP reports on the Corrective Action Investigation that was conducted for the CAU, which included characterization and modeling. It also presents the recommended corrective actions to address the objective of protecting human health and the environment. The recommended corrective action alternative is “Closure in Place with Modeling, Monitoring, and Institutional Controls.” The role of monitoring is to verify that Contaminants of Concern (COCs) have not exceeded the Safe Drinking Water Act (SDWA) limits (Code of Federal Regulations, 2014) at the regulatory boundary, to ensure that institutional controls are adequate, and to monitor for changed conditions that could affect the closure conditions. The long-term closure monitoring program will be planned and implemented as part of the Closure Report stage after activities specified in the CADD/CAP are complete. Groundwater at the NNSS has been monitored for decades through a variety of programs. Current activities were recently consolidated in an NNSS Integrated Sampling Plan (DOE, 2014). Although monitoring directed by the plan is not intended to meet the FFACO long-term monitoring requirements for a CAU (which will be defined in the Closure Report), the objective to ensure public health protection is similar. It is expected that data collected in accordance with the plan will support the transition to long-term monitoring at each CAU. The sampling plan is designed to ensure that monitoring activities occur in compliance with the UGTA Quality Assurance Plan (DOE, 2012). The sampling plan should be referenced for Quality Assurance (QA) elements and procedures governing sampling activities. The NNSS Integrated Sampling Plan specifies the groundwater monitoring that will occur in CAU 98 until the long-term monitoring program is approved in the Closure Report. The plan specifies the wells that must be monitored and categorizes them by their sampling objective with the associated analytical requirements and frequency. Possible sample collection methods and required standard operating procedures are also presented. The intent of this handbook is to augment the NNSS Integrated Sampling Plan by providing well-specific details for the sampling professional implementing the Sampling Plan in CAU 98, Frenchman Flat. This handbook includes each CAU 98 well designated for sampling in the NNSS Integrated Sampling Plan. The following information is provided in the individual well sections: 1. The purpose of sampling. 2. A physical description of the well. 3. The chemical characteristics of the formation water. 4. Recommended protocols for purging and sampling. The well-specific information has been gathered from numerous historical and current sources cited in each section, but two particularly valuable resources merit special mention. These are the USGS NNSS website (http://nevada.usgs.gov/doe_nv/ntsarea5.cfm) and the UGTA Field Operations website (https://ugta.nv.doe.gov/sites/Field%20Operations/default.aspx). 2 Land surface elevation and measuring point for water level measurements in Frenchman Flat were a focus during CAU investigations (see Appendix B, Attachment 1 in Navarro-Intera, 2014). Both websites listed above provide information on the accepted datum for each well. A summary is found on the home page for the well on the USGS website. Additional information is available through a link in the “Available Data” section to an “MP diagram” with a photo annotated with the datum information. On the UGTA Field Operations well page, the same information is in the “Wellhead Diagram” link. Well RNM-2s does not have an annotated photo at this time. All of the CAU 98 monitoring wells are located within Area 5 of Frenchman Flat, with the exception of ER-11-2 in Area 11 (Figure 1). The wells are clustered in two areas: the northern area (Figure 2) and the central area (Figure 3). Each well is discussed below in geographic order from north to south as follows: ER-11-2, ER-5-3 shallow piezometer, ER-5-3-2, ER-5-5, RNM-1, RNM-2s, and UE-5n.

(1996↗

DOE OSTI2016

The concentrations of radionuclides, heavy metals, and poloychlorinated biphenyls in field mice collected from regional background areas. Revision 3

Field mice are effective indicators of contaminant presence. This paper reports the concentrations of various radionuclides, heavy metals, polychlorinated biphenyls, high explosives, perchlorate, and dioxin/furans in field mice (mostly deer mice) collected from regional background areas in northern New Mexico. These data, represented as the regional statistical reference level (the mean plus three standard deviations = 99% confidence level), are used to compare with data from field mice collected from areas potentially impacted by Laboratory operations, as per the Environmental Surveillance Program at Los Alamos National Laboratory.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

Residential Cooking Behavior in the United States: Data Collected from a Web-Based Survey

Cooking has a significant impact on indoor air quality. When cooking occurs, how foods are cooked, and the types of food that are cooked have all been shown to impact the rate at which occupants are exposed to pollutants. Home occupancy characteristics impact how concentrations in the home translate into exposures for the occupants. With the intent of expanding our understanding of cooking behavior in the U.S., we developed and advertised an online survey to collect household cooking behavior for the 24 hrs prior to taking the survey. The survey questions were designed to address gaps in knowledge needed to predict the impact of cooking on indoor concentrations of PM2.5 and other pollutants. The survey included the following questions: 1) which meals households ate at home; 2) number of household members at home during cooking; 3) the type of oil used for cooking; 4) the type of foods cooked at each meal; 5) the type of cooking devices used; and 6) the methods selected for food preparation. We also collected information on household characteristics such as their location (zip code), ethnicity, and ages of family members. We analyzed the variability in home cooking characteristics for households in different climate zones and with four different types of family compositions: 1 senior living alone, 1 adult living alone, 2 or more adults/seniors, and families with children. We used simple statistical tests to determine if the probability of certain cooking behaviors differed between these subgroups.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2016

Solar Technology Test, Evaluation, and Data Collection: Cooperative Research and Development Final Report, CRADA Number CRD-08-279

Under this Agreement, NREL will work with Abengoa Solar Inc. on the testing, evaluation, and collection of data related to Abengoa Solar Inc. solar technologies and systems. This work includes, but is not limited to, testing and evaluation of solar component and system technologies, data collection and monitoring, performance evaluation, reliability testing, thermal energy storage integration, solar resource measurement and forecasting, grid impact testing, and analysis. This work will be conducted at NREL, SolarTAC (Aurora), and other field test locations.

14 SOLAR ENERGY↗

DOE OSTI2016

ACAPEX – Ship-Based Ice Nuclei Collections Field Campaign Report

Measurements were sought to evaluate a hypotheses that sea-spray-sourced ice-nucleating particles (INPs) are of biological origin and represent a distinctly different INP population in comparison to long-range-transported desert or urban and regional land-sourced INP, and that the layering of marine within other aerosol layers feeding orographic storms over the mountains of California and the Western United States thereby leads to common and quantifiable scenarios that influence precipitation over the region. Aerosol collections on the National Oceanic and Atmospheric Administration (NOAA) research vessel (RV) Ronald H. Brown, for subsequent processing of INP immersion freezing activation temperature spectra and composition analyses, added a valuable measurement component to the ARM Cloud Aerosol Precipitation Experiment (ACAPEX) and related CalWater2 (NOAA) studies for use in parameterizing and modeling the impacts of marine boundary layer and other aerosols on climate and radiation via aerosol indirect effects on mixed-phase clouds. Twenty-five nominally 24-hour collections were made and have been processed for immersion freezing INP number concentrations versus temperature in the mixed-phase cloud temperature regime from -10 to -27°C. The similarity of INP number concentrations compared to typical marine boundary layer values attributed to sea-spray aerosols was noted. Nevertheless, variability of INP concentrations of up to 50 times was noted at individual temperatures over the course of the study. A particular analysis possible with this data set is to examine INP budgets over oceans inside versus outside of atmospheric river conditions. These INP measurements supplemented multiple airborne INP measurements on the ARM Aerial Facility (AAF), and others on the ground during ACAPEX and CalWater2, to provide extensive spatial and temporal analyses of INP immersion freezing spectra during winter storm periods. Future analyses will use thermal sensitivity to examine INP compositions as organic versus inorganic in these marine boundary layer samples. Data set integration is occurring under funding from an Atmospheric System Research (ASR) proposal.

54 ENVIRONMENTAL SCIENCES↗