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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Effectiveness of Residue and Tillage Management on Runoff Pollutant Reduction from Agricultural Areas

Highlights No-till and no-till residue systems were effective in reducing runoff particulate and total nutrients but increased dissolved nutrients. Maintaining >30% residue cover reduced most runoff constituents, irrespective of no-till or tillage. No-till-residue prevented runoff nutrient losses and benefitted farm revenue by avoiding tillage. Abstract. Reduced tillage management conservation practices (No-till and Reduced-till) are widely adopted in agriculture; however, understanding their overall effectiveness for water quality protection is challenging. A meta-analysis was conducted to understand and quantify the effectiveness of residue and tillage management on runoff, sediment, and nutrient losses from agricultural fields. Annual runoff and the associated sediment, and nutrient (nitrogen and phosphorus) loads were compiled from 60 peer reviewed research articles published across the United States and Canada. A total of 1575 site-years of data were categorized into tillage (<30% surface cover), no-tillage (<30% surface cover), tillage with residue (>30% surface cover), no-tillage with residue (>30% surface cover), and pasture management. No-tillage, no-tillage-residue, and tillage-residue managements were evaluated for their effectiveness in reducing runoff, nutrients, and sediment loads compared to tillage. Synthesized and surveyed corn yield data were used to evaluate the economic cost effectiveness of no-tillage-residue management with respect to tillage. Across the site years (1968-2019) studied, median runoff depth for no-tillage and no-tillage-residue were 84% and 70% greater than tillage and tillage-residue management, respectively. No-tillage-residue management had up to 86% less sediment losses than tillage systems, on average, for both >30% and <30% surface cover. No-tillage-residue management was most effective, with a positive performance effectiveness of 65% to 90% in controlling sediments, particulate, and total nutrient losses in runoff compared to tillage. Cost effectiveness analysis revealed the benefits of no-tillage-residue management in reducing nutrient loads and increasing net-farm revenue by avoiding tillage operational costs. Except for dissolved phosphorus, no-tillage-residue management cost effectiveness for sediments and nutrient loads ranged from negative $6 to negative $102 per every Mg or kg of load reduction, indicating it had both economic and environmental benefits compared to tillage management. Overall, these results indicate that over the long-term, no-tillage and tillage, combined with greater than 30% residue cover, can effectively reduce sediment and nutrient losses. This work highlights the importance of crop residues on the soil surface to reduce runoff losses, even in no-tillage systems. Keywords: Conservation tillage, No-tillage, Residue cover, Tillage, Water quality.

Agriculture↗
DOE OSTI2026

Lake-Effect Snowstorm Events and Associated Snowfall Totals Integrated from NOAA Storm Reports, ERA5, and HRRR for the Laurentian Great Lakes (1997–2024)

Lake-effect snowstorms are localized, impactful winter weather phenomena that can generate substantial snowfall totals and pose significant challenges for forecasting, transportation, and regional infrastructure. To support the analysis and modeling of these events, this dataset compiles observational reports of lake-effect snowstorms alongside corresponding snowfall estimates derived from gridded atmospheric datasets. The observational component of the data originates from the National Weather Service (NWS) winter storm report, subset to lake-effect snow event type, covering 1997–2024. For each lake-effect snow event, this data provides the impacted county, event start and end datetimes at an hourly resolution, as well as relevant storm narratives. The complementary reanalysis-derived data is sourced from European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) and High-Resolution Rapid Refresh (HRRR) gridded data. For both gridded datasets, the maximum total snowfall (in units mm) was extracted, constrained by the county and datetimes specified by the observational report. ERA5 data covers the entire observational period (1997–2024), whereas HRRR data is only available from November 2016 – December 2024. Three CSV files are provided here: (1) the observational lake-effect snow event report, (2) ERA5 maximum snowfall detections for each event, and (3) HRRR maximum snowfall detections for each event. Relevant data from the observational files, such as impacted state and county, event datetimes, and event IDs, were included for convenience. Users can inspect and visualize the data using tools such as Microsoft Excel and Python pandas/matplotlib packages. This dataset may support a variety of applications, including climatological analyses of lake-effect snowfall, evaluation of snowfall representation in atmospheric datasets and numerical weather prediction models, and the development of machine learning approaches for detecting or predicting lake-effect snowfall events.

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > SOLID↗
DOE OSTI2023

On Magnitudes and Inferred Yields of the 39 Underground Nuclear Test Explosions at the Novaya Zemlya Test Site

ABSTRACT We review the previously compiled seismic magnitudes for underground nuclear explosions at the Union of the Soviet Socialist Republics Novaya Zemlya Test Site, and analyze these data in the context of published details about individual tests and official Russian reports of annual cumulative explosive energy release at the test site. We derive relationships between teleseismic body wave magnitude mb and explosive yield Y by predicting the yield of each test using mb and minimizing the difference between predicted and reported annual cumulative yield. A linear relationship between mb and logY with a slope of 0.82 provides a good fit to the annual total yield, with a root mean square (rms) misfit of 0.095 logY units. A spectral magnitude relationship based on the explosion source model of Mueller and Murphy (1971) with a single-free-parameter provides a slightly better fit. For the 10 tests for which individual yields can be directly deduced from the official reports, the rms misfit of reported yields is less than 0.1 logY units or about 25%. More complex relationships that differentiate between the northern and southern test areas, or take account of variations in the scaled depth of burial, do not provide substantially better fits to the reported yields.

Geochemistry & Geophysics↗
DOE OSTI2021

Simulated hydrological dynamics and coupled iron redox cycling impact methane production in an Arctic soil: Modeling Archive

This Modeling Archive is in support of an NGEE Arctic publication "Simulated hydrological dynamics and coupled iron redox cycling impact methane production in an Arctic soil" in the Journal of Geophysical Research-Biogeosciences. We simulated biogeochemical cycling in arctic soils using the PFLOTRAN geochemical model combined with measurements from previous NGEE Arctic incubations of polygonal permafrost soils in northern Alaska (Zheng et al., 2018). Simulated iron cycling, carbon dioxide production, and methane production were compared with incubation measurements and the parameterized model was then used to simulate coupled iron and carbon cycling over repeated oxic-anoxic cycles at different levels of carbon substrate availability and pH. The most recent data version (2.0) in the archive incorporates changes to the model and simulations as suggested by reviewers during the manuscript review process. These changes include an updated parameterization of the model; a new set of simulations omitting the iron cycle for direct evaluation of how iron cycle processes affect modeled outcomes; and a set of simulations testing different scenarios of carbon substrate availability in addition to scenarios of initial soil pH. This archive contains simulation code, model output, and analysis code for PFLOTRAN simulations. All scripts are python except the batch script for submitting multiprocessor jobs. Note that the model also requires compiled versions of the Alquimia interface and the NGEE Arctic fork of the PFLOTRAN geochemical simulator (see the README_INSTALL document for basic instructions). The Output directory contains eight data files in netCDF format generated by the model. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

On the Marriage of Asynchronous Many Task Runtimes and Big Data: A Glance

The rise of the accelerator-based architectures and reconfigurable computing have showcased the weakness of software stack toolchains that still maintain a static view of the hardware instead of relying on a symbiotic relationship between static (e.g., compilers) and dynamic tools (e.g., runtimes). In the past decades, this need has given rise to adaptive runtimes with increasingly finer computational tasks. These finer tasks help to take advantage of the hardware by switching out when a long latency operation is encountered (because of the deeper memory hierarchies and new memory technologies that might target streaming instead of random access), thus trading off idle time for unrelated work. Examples of these finer task runtimes are Asynchronous Many Task (AMT) runtimes, in which highly efficient computational graphs run on a variety of hardware. Due to its inherent latency tolerant characteristics, Latency-sensitive applications, such as Graph Analytics and Big Data can effectively use these runtimes. This paper aims to present an example of how the careful design of an AMT can exploit the hardware substrate when faced with high latency applications such as the ones given in the Big Data domain. Moreover, with its introspection and adaptive capabilities, we aim to show the power of these runtimes when facing the changing requirements of the application workloads. We use the Performance Open Community Runtime (P-OCR) as our vehicle to demonstrate the concepts presented here.

adaptive runtime, big data analysis↗
DOE OSTI2025

The Vertebrate Breed Ontology: Toward Effective Breed Data Standardization

Abstract Background Limited universally-adopted data standards in veterinary medicine hinder data interoperability and therefore integration and comparison; this ultimately impedes the application of existing information-based tools to support advancement in diagnostics, treatments, and precision medicine. Hypothesis/Objectives A single, coherent, logic-based standard for documenting breed names in health, production, and research-related records will improve data use capabilities in veterinary and comparative medicine. Animals No live animals were used. Methods The Vertebrate Breed Ontology (VBO) was created from breed names and related information compiled from the Food and Agriculture Organization of the United Nations, breed registries, communities, and experts, using manual and computational approaches. Each breed is represented by a VBO term that includes breed information and provenance as metadata. VBO terms are classified using description logic to allow computational applications and Artificial Intelligence–readiness. Results VBO is an open, community-driven ontology representing over 19 500 livestock and companion animal breed concepts covering 49 species. Breeds are classified based on community and expert conventions (e.g., cattle breed) and supported by relations to the breed's genus and species indicated by National Center for Biotechnology Information (NCBI) Taxonomy terms. Relationships between VBO terms (e.g., relating breeds to their foundation stock) provide additional context to support advanced data analytics. VBO term metadata includes synonyms, breed identifiers/codes, and attributed cross-references to other databases. Conclusion and Clinical Importance The adoption of VBO as a standard for breed names in databases and veterinary electronic health records enhances veterinary data interoperability and computability, supporting precision medicine.

Veterinary Sciences↗
DOE OSTI2020

Compilation and Evaluation of Beta-Delayed Neutron Emission Probabilities and Half-Lives for Z > 28 Precursors

We present a compilation and evaluation of experimental β-delayed neutron emission probabilities (P n ) and half-lives (T 1/2 ) for known or potential β-delayed neutron precursors with atomic number Z >28 ( 73 Cu – 233 Fr). This article includes the recommended values of both of these quantities, together with a compilation of experimental measurements when available. Some notable cases, as well as proposed standards forβ-delayed neutron measurements are also discussed. Evaluated data has also been compared to systematics using three different approaches.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

LANL Regular Employee Population and Demographics, FY15-21

This document summarizes an effort to compile and analyze the LANL regular employee population’s demographic attributes and trends between FY15-FY21 using MicroStrategy, a web-based data analytics and visualization tool. LANL’s HR Division collected and prepared data for the Weapons Program’s annual reporting activities for the 2017 through 2023 NNSA Stockpile Stewardship and Management Plan (SSMP). Los Alamos workforce data represent the fiscal year-end snapshot of the permanent employee population who are categorized by the Common Occupational Classification System (COCS). This work enables further analyses, including trends for all workforce attributes presented in the SSMPs as well as a definition of a crosswalk between COCS categorization and the internal laboratory job classification hierarchy. Data for other sites and the federal workforce, as shown in the SSMPs, are included and corresponding figures can be visualized within the MicroStrategy tool. A portable, Excel-based version of the tool was developed and shared with the multi-site workforce working group. This summary highlights selected aspects of the LANL regular workforce. The data analyses and visualizations communicate insights within three major themes regarding permanent LANL employees: 1) demographic transformation, 2) attrition, and 3) skills. Regarding demographic transformation, and consistent with the general trend across the enterprise, early career regular employees are the fastest growing group, with growth ranging between 12-34% year-to-year over the seven-year period analyzed. The data also reflect effects of internal and external factors on attrition; the large spike in separations in FY18 aligns with the contract transition from LANS to Triad and the dip in attrition between FY20-FY21 is likely a result of the global pandemic. The population of regular employees in general management, engineer, and operator COCS categories have the fastest growth rates amongst all the occupational categories. The MicroStrategy and Excel tools provide additional details and trends.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Reservoir Thermal Energy Storage Benchmarking (Rev. 3)

A benchmarking analysis of RTES research funded by GTO through the Beyond Batteries projects was conducted against the ESGC to see where they fit within the identified ESGC Use Cases. The projects were found to advance knowledge in multiple ESGC use cases, either directly or in some cases, indirectly as enabling technologies. This analysis is helpful to understand where RTES and associated research fits into the larger discussion around energy storage technologies. Also, a retrospective analysis of the Beyond Batteries projects was conducted to evaluate what the projects learned and how the results can be applied to advance the value of RTES. Major results of each of the studies are summarized in Table 2. Additionally, a comparative metrics analysis for RTES was completed to understand where RTES lies within the energy storage industry. Metrics for evaluation of RTES and its comparison to other storage technologies were selected and ranges of their values compiled. The selected metrics – LCOE (levelized cost of energy), capital costs, roundtrip efficiency, energy storage capacity, and storage time – were chosen based on data availability and have a particularly strong influence on the potential deployment of a storage technology. Charts which compare the metrics are presented in section 4.3 and show ranges for each of the 10 selected technologies. However, due to a lack of domestic operational facilities, values for RTES and for portions of the remaining technologies are based on theoretical modeling and studies of best-case scenarios. LCOE estimates for RTES fall within the lower reaches of Figure 15, but nevertheless amount to 2 – 5 times the ESGC Roadmap goal for LCOE, for example in the Facilitating and Evolving Grid Use Case. Capital costs for RTES sit on the higher end (Figure 16) but are expected to decrease as new projects are developed and the technology is refined. The theoretical roundtrip efficiency reported for RTES varies from mid to high percentages (Figure 17) with efficiencies upwards of 93% in modeled scenarios in the Portland Basin (Bershaw et al.,2020). RTES is also expected to have the largest energy storage capacities and longest storage times, likely matched only by lower efficiency hydrogen storage. To better assess the role that RTES could play in energy storage we examined it’s potential in the U.S. The potential depends on many factors. Recently, many researchers have started looking at deep sedimentary basins, depleted oil and gas fields, and basalt formations as potential targets for RTES development. The United States Geological Survey (USGS) has analyzed various cities and shown substantial RTES potential in the cooling sector (Pepin et al., 2021). By modeling RTES in low-quality groundwater (e.g., brackish), it is shown to be favorable across the U.S. with particular suitability in the Illinois Basin, Coastal Plains, and Basin and Range regions. Seasonal RTES operations have also been modeled in the Portland Basin by those at the USGS and Portland State University to simulate an RTES system supplying heating loads needed for the Oregon Health and Science University. Simulations suggest that high conductive heat loss in the initial years exists but tends to decrease with increasing time and development of the resource due to self-insulating nature of the basalts (Burns et al., 2020). Other national laboratory efforts are taking a close look at many of the technical issues involved with RTES (McLing et al., 2019, McLing et al., 2022). These include difficulties in understanding geochemical, hydrogeological, mechanical, and microbiological changes at such elevated temperatures and operational scenarios. Major gaps in research are identified and suggested for future work. With this increased focus to understand how to make RTES successful in the U.S., this technology could be a potential solution to many of the nation’s energy storage problems. For the energy independence of this country, the DOE should prioritize de-risking this technology by making future investments in pilot-scale demonstrations to attract potential investors.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

CQNN: a CGRA-based QNN Framework

We propose a novel Coarse-Grained Reconfigurable Architecture-based (CGRA) QNN acceleration framework, CQNN. CQNN has a large number of basic components for binary functions. By programming CQNN at runtime according to the target QNN models, these basic components are integrated efficiently to support QNN functions with any data-width and hyper-parameter requirements and CQNN is reconfigured to have the optimal architecture for the target models. The framework includes compiler, architecture design, simulator and RTL generator. Experimental results show CQNNs can complete the inference of AlexNet and VGG-16 within 0.13ms and 2.63ms.

Geng, Tong↗
DOE OSTI2022

An ecological niche model to predict the geographic distribution of Haemagogus janthinomys, Dyar, 1921 a yellow fever and Mayaro virus vector, in South America

Yellow fever virus (YFV) has a long history of impacting human health in South America. Mayaro virus (MAYV) is an emerging arbovirus of public health concern in the Neotropics and its full impact is yet unknown. Both YFV and MAYV are primarily maintained via a sylvatic transmission cycle but can be opportunistically transmitted to humans by the bites of infected forest dwelling Haemagogus janthinomys Dyar, 1921. To better understand the potential risk of YFV and MAYV transmission to humans, a more detailed understanding of this vector species’ distribution is critical. This study compiled a comprehensive database of 177 unique Hg . janthinomys collection sites retrieved from the published literature, digitized museum specimens and publicly accessible mosquito surveillance data. Covariate analysis was performed to optimize a selection of environmental (topographic and bioclimatic) variables associated with predicting habitat suitability, and species distributions modelled across South America using a maximum entropy (MaxEnt) approach. Our results indicate that suitable habitat for Hg . janthinomys can be found across forested regions of South America including the Atlantic forests and interior Amazon.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Foliar element determination from field survey in association with the National Ecological Observatory Network Airborne Observation Platform survey, East River, Colorado 2018

The purpose of this dataset is to support research aimed at understanding the coupling between hydrologic and biogeochemical processes at watershed scale, particularly the relationship between aboveground vegetation characteristics and subsurface soil properties. These data are intended to inform and calibrate models of catchment-scale biogeochemical fluxes, including rock-derived nutrient cycling, and they were procured to address the following questions: (1) What is the distribution of vegetation characteristics across the study catchments? (2) Are foliar concentrations of rock-derived nutrients related to underlying lithology and soil availability, or are these signals masked by biotic nutrient cycling and retention processes?This data package contains foliar elemental data collected during the 2018 National Ecological Observatory Networks (NEON) Airborne Observation Platform (AOP) imaging spectroscopy and lidar surveys in Gunnison County, Colorado. Folair samples were collected across the East River, Washington Gulch, Slate River, and Coal Creek watersheds and contain a mixture of vegetation including meadow, shrub, and tree foliar samples. The samples were processed using aqua regia digestion and analyzed for elemental determination on inductively coupled plasma optical emission spectrometry (ICP-OES).The data package includes: (1) raw foliar elemental data files in CSV and PDF formats, (2) quality control certificates in PDF format, and (3) an aggregated CSV file containing all elemental measurements compiled across samples. No specialized software is required to access or use these files.

2018 National Ecological Observatory Network Campa↗
DOE OSTI2022

Corrective Action Unit 98: Frenchman Flat Five-Year Evaluation Nevada National Security Site, Nevada (Revision 1)

The Corrective Action Unit (CAU) 98, Frenchman Flat (FF) Closure Report (CR) (NNSA/NFO, 2016) and its ensuing Records of Technical Change (ROTCs) (compiled in DOE/EMNV, 2019) required the U.S. Department of Energy (DOE), Environmental Management (EM) Nevada Program’s Underground Test Area (UGTA) Activity to collect data for five years to establish triggers for the monitoring network and analyze the monitoring points for viability in long-term monitoring. This document provides the results of the five-year evaluation and presents recommendations for future monitoring of CAU 98.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

LANL Workforce Reporting Tool

The LANL Workforce Reporting Tool compiles and analyzes workforce demographics and attributes as presented in the annual Stockpile and Stewardship Management Plan (SSMP) over FY15-21 using MicroStrategy, a data analytics and visualization software. There are three major employee populations included in the tool: 1) LANL’s regular (permanent) employees; 2) LANL’s entire workforce (regular, craft, contractors, students, post doctorate students, limited term employees, and lab associates); 3) The Nuclear Security Enterprise’s (NSE) permanent career employees (combined and site-by-site).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

R -Matrix Analysis and Statistical Properties of Dysprosium Isotopes in the Neutron Energy Ranges Up To A Few Kev

In support of the Nuclear Criticality Safety Program, a set of evaluated resonance parameters was generated for seven dysprosium isotopes in the neutron energy range from thermal up to a few keV. The evaluation methodology used the Reich-Moore approximation to fit, with the R-matrix code SAMMY, the high-resolution capture and transmission measurements on natural and enriched samples recently performed at the Rensselaer Polytechnic Institute Gaerttner LINear ACcelerator facility. Additional transmission data measured on enriched samples by Liou at the Columbia University Nevis synchrocyclotron in the mid-seventies were used to gauge the neutron widths above 15 eV. Thermal constants such as absorption and (in)coherent scattering cross sections and corresponding scattering lengths were calibrated to the National Institute of Standards and Technology’s compilation except for 161,164 Dy isotopes.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Spiner-EOSPAC Comparison: performance and accuracy on Power9 CPU and GPU

The goal of this report is to concisely compare EOSPAC to Spiner EOS for a selection of commonly-used materials over as much of their domain as is possible. Importantly, this comparison does not address the way that the Euler equations may amplify interpolation errors and we take as given that the rational function interpolator gives the best possible representation of the EOS represented by the Sesame data. Neither does the report address all, or even majority of, the capabilities of each code nor does it explore performance or accuracy over multiple compilers and platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Literature Review Investigating Historical Plutonium Solubility in SRS Tank Waste

The Savannah River Site (SRS) has designed the Accelerated Basin De-inventory (ABD) program to accelerate the de-inventory of L-Basin and accelerate the Spent Nuclear Fuel (SNF) disposition mission. Similarly, the H-Canyon facility at SRS is reestablishing the 6.3D electrolytic dissolver for dissolving unirradiated stainless-steel (SS) clad Fast Critical Assembly (FCA) fuel. In both discard types (ABD and FCA), plutonium is present and its complex solubility when composited to Concentration, Storage, and Transfer Facility (CSTF) sludge is being investigated as it may have downstream impacts to the liquid waste (LW) organization. This literature review aims to highlight and compile the existing literature on plutonium solubility in waste streams relevant to ABD and FCA discards, as well as discuss some considerations in analyzing solubility data of plutonium. This review serves to help define the analysis methods for future experiments involving plutonium (and other actinides) and in designing appropriate testing conditions surrounding these studies. This review is broken up into five parts and will discuss: (i) The possible effects of testing hold time and temperature on plutonium solubility, (ii) the influence of neutralization rate and particle size of freshly precipitated discards, (iii) the coprecipitation of plutonium with iron and uranium, (iv) predictive solubility modeling and the influence of supernate anions on solubility, and (v) the speciation of plutonium in solutionas a result of supernate anions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

EMP - Environmental Radiological Air Monitoring Plan: PNNL Operations in Washington

The Environmental Radiological Air Monitoring Plan (EMP) for Pacific Northwest National Laboratory (PNNL) describes systems/processes/practices related to radiological operations in Richland and Sequim, Washington, that are associated with environmental radiological air monitoring and surveillance activities. The activities described support the lab’s responsibility to maintain safe operations and minimize negative impacts to both onsite and offsite persons and environment. Dose assessments required by regulations and DOE Orders for the public and biota are described. PNNL conducts environmental air surveillance monitoring as part of the PNNL Site Radioactive Air Emissions License (RAEL)-005 for Richland Campus, issued in 2010 with its most recent renewal effective in January 2021. The radioactive air emissions license for the PNNL-Sequim campus (RAEL-014) was issued to the U.S. Department of Energy in 2012 with its most recent renewal effective in January 2023. The EMP is a compilation of the following four documents: - Environmental Radiological Air Monitoring Plan (this main document) (PNNL-20919) - Sampling and Analysis Plan (Attachment 1) (PNNL-20919-1) - Data Management Plan (Attachment 2) (PNNL-20919-2) - Dose Assessment Guidance (Attachment 3) (PNNL-20919-3).

40 CFR 61 Subpart H↗