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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Groundwater Monitoring Report, U.S. Department of Energy Y-12 National Security Complex, Oak Ridge, Tennessee

This report contains the groundwater and surface water monitoring data obtained during calendar year (CY) 2019 at the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) on the DOE Oak Ridge Reservation (ORR) in Oak Ridge, Tennessee. The monitoring data were obtained from wells, springs, and surface water sampling locations in three hydrogeologic regimes at Y-12. The Bear Creek Hydrogeologic Regime (Bear Creek Regime) encompasses a section of Bear Creek Valley (BCV) between the west end of Y-12 and the west end of the Bear Creek Watershed (directions are in reference to the Y-12 grid system, shown as Plant North. The Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime) encompasses the Y-12 industrial facilities and support structures in BCV. The Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime) encompasses a section of Chestnut Ridge directly south of Y-12. Background information in Section 2 of this report outlines the hydrogeologic framework for groundwater and surface water quality monitoring at Y-12 and includes an overview of the groundwater contamination in each hydrogeologic regime. Section 3 provides details regarding the groundwater and surface water sampling and analysis activities implemented under the Y-12 GWPP, including sampling locations and frequency, sample collection and handling, field measurements and laboratory analytes, quality assurance (QA)/quality control (QC) sampling, data management, and data quality assessment (DQA). However, the equivalent QA/QC or DQA information for the groundwater and surface water data associated with the monitoring programs implemented by UCOR are not included in this report and instead are deferred to referenced programmatic plans and reports issued by OREM and UCOR. Section 4 of this report presents a summary evaluation of the CY 2019 monitoring data with regard to the respective objectives of surveillance monitoring and exit pathway/perimeter monitoring. The evaluation is based primarily on the analytical results for the following principal groundwater contaminants at Y-12: nitrate, uranium, gross alpha activity, gross beta activity, and volatile organic compounds (VOCs). Section 5 summarizes the most significant findings with respect to the principal contaminants along with recommendations for any proposed changes to the ongoing groundwater and surface water quality monitoring performed under the Y-12 GWPP. Technical reports and plans cited in the narrative sections of the report are listed in Section 6. Narrative sections of this report reference several appendices. Figures (maps and diagrams) and data tables (excluding data summary tables incorporated in the narrative sections) are in Appendix A and Appendix B, respectively. Appendix C contains construction details for each well sampled during CY 2019 by either the Y-12 GWPP or UCOR, along with schematic diagrams for wells equipped with Westbay™ multiport sampling equipment or Barcad® pump systems. Appendix D supports the background summary discussion in Section 2 and provides more detailed information about the hydrogeologic framework for groundwater and surface water monitoring at Y-12, including the primary sources of groundwater contamination in each hydrogeologic regime. Results for all field measurements and laboratory analyses obtained by the Y-12 GWPP and UCOR are presented in Appendix E, which also includes the sample numbers for the QA/QC samples associated with groundwater and surface water monitoring performed by the Y-12 GWPP.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Satellite global monitoring of environmental quality

The missions of two NASA satellites for the monitoring of environmental quality are described: Nimbus G, the Air Pollution and Oceanographic Observing Satellite, and the Applications Explorer Mission (AEM) satellite to be used in the Stratospheric Aerosol and Gas Experiment (SAGE). The scientific payload of Nimbus G is described in detail with a discussion of limb infrared monitoring of the stratosphere, the stratospheric and mesospheric sounder, stratospheric aerosol measurement, the solar and backscatter UV spectrometer for ozone mapping, the earth radiation budget experiment, the scanning multichannel microwave radiometer, the coastal zone color scanner and the temperature-humidity infrared radiometer. A brief description is given of the SAGE program and future NASA plans relating to the global monitoring of environmental quality are outlined.

Schiffer, R. A.↗
DOE OSTI2020

Lessons Learned in the Development of Industry Guidance - 20279

The availability of industry guidance on different aspects of waste management forms a valuable reference for waste practitioners. The guidance typically details the principles, processes and practices that should be consulted during each stage of the relevant activities. It also includes relevant regulatory and international requirements, appropriate case studies and examples of best practices to illustrate technical concepts and make the information available to the reader in an accessible manner. Over recent years Wood have developed (or are developing) a number of industry guidance documents on a range of topics including Solid Waste Characterization, Routine Water Quality Monitoring on Nuclear Sites: Pipeline Characterization: Determining Background Radioactivity for Land Quality Assessment: Interim Storage and Aqueous Waste Management. This talk provides an overview of lessons learned along the way including: - the importance of stakeholder engagement through the process: - how to identify 'good practice'; - the importance of iterative development; and - the selection of illustrative and informative case studies. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2022

NASA's Next Generation of Atmospheric Data Science

The Multi-Angle Imager for Aerosols (MAIA) and the Tropospheric Emission: Monitoring of Pollution(TEMPO) are NASA’s next-generation satellite missions for air quality monitoring. These missions will produce high-quality, high-resolution air quality data to support cross-displinary research. The MAIA mission is collaborating with health science researchers and epidemiologists to study the impacts of air quality on health outcomes. TEMPO aims to improve our understanding of tropospheric air pollution chemistry and our ability to make predictions about air quality and climate forcing. TEMPO will offer hourly measurements of tropospheric ozone, aerosols, and clouds focused on North America at high-spatial resolution, while MAIA will produce high-resolution measurements of speciated particulate matter targeting densely populated cities around the globe. Data from these missions will help improve our understanding of the sources, types, and interactions among the aerosols and trace gases that are polluting Earth’s atmosphere, as well as our understanding of the impact of air pollution on pollution on a wide range of important areas including human health, agriculture, weather, and climate change. The challenges of cross-disciplinary research, computationally expensive multi-variate analyses, and high-resolution data at both local and global scales are driving substantial changes across all of NASA’s Distributed Active Archive Centers (DAACs). High resolution data at scales such these requires a new approach to data ingest, archive, and publication. Like other NASA DAACs, the Atmospheric Science Data Center (ASDC), the DAAC that will be responsible for publishing MAIA and TEMPO data products has historically archived and distributed data on premise. DAACs of the future will archive and distribute data in the cloud, enabling them to remake themselves as research-focused data centers that will support on-demand, data-intensive computations for highly accurate retrospective analyses and predictions. Under the new paradigm, data formats and metadata must support on-demand spatial and temporal sub-setting, as well as other data transformation services such as re-gridding and re-sampling. This presentation will discuss work being done to address data formatting and metadata requirements in this dynamic new environment. In addition to the changes in data stewardship practices at the ASDC, the increased focus on supporting scientific research is driving changes in the relationship between DAACs and researchers. While the ASDC will continue to provide first rate data management and stewardship, it is increasingly focused on serving as a partner not only to the science teams that gather and produce the data it publishes, but to the researchers that use that data.

Beth Huffer↗
NASA NTRS1988

PI-in-a-box: Intelligent onboard assistance for spaceborne experiments in vestibular physiology

In construction is a knowledge-based system that will aid astronauts in the performance of vestibular experiments in two ways: it will provide real-time monitoring and control of signals and it will optimize the quality of the data obtained, by helping the mission specialists and payload specialists make decisions that are normally the province of a principal investigator, hence the name PI-in-a-box. An important and desirable side-effect of this tool will be to make the astronauts more productive and better integrated members of the scientific team. The vestibular experiments are planned by Prof. Larry Young of MIT, whose team has already performed similar experiments in Spacelab missions SL-1 and D-1, and has experiments planned for SLS-1 and SLS-2. The knowledge-based system development work, performed in collaboration with MIT, Stanford University, and the NASA-Ames Research Center, addresses six major related functions: (1) signal quality monitoring; (2) fault diagnosis; (3) signal analysis; (4) interesting-case detection; (5) experiment replanning; and (6) integration of all of these functions within a real-time data acquisition environment. Initial prototyping work has been done in functions (1) through (4).

Colombano, Silvano↗
NASA NTRS2016

Watershed-Scale Modeling of Land-Use and Altered Environment Impacts on Aquatic Weed Growth in the Delta

The California Sacramento-San Joaquin River Delta is the hub for California's water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, and water quality have all been suspected as playing role in the dramatic expansion of invasive aquatic plants and their impact on ecosystems of the San Francisco Bay / California Delta complex. NASA Ames Research Center, USDA-Agricultural Research Service, the State of California, UC Davis, and local governments have partnered under a USDA sponsored project (DRAAWP) to develop science-based, adaptive-management strategies for invasive aquatic plants in Sacramento-San Joaquin Delta. Critical to developing management strategies is to understand how the Delta is affected by both the magnitude of fluctuations in land-use and climate / drought induced altered environments and how the plants respond to these altered environments. We utilize the Soil Water Assessment Tool (SWAT), a watershed-scale model developed to quantify the impact of land management practices in large and complex watersheds on water quality, as the backbone for a customized Delta model - Delta-SWAT. The model uses land-use, soils, elevation, and hydrologic routing to characterize pesticide and nutrient transport from the Sacramento and San Joaquin rivers watersheds and loading into the Delta. Land-use within the Delta, as well as water extraction to supply those functions, and the resulting return of water to Delta waterways are included in Delta-SWAT. Hydrologic transport within the Delta has required significant attention to address the lack of elevation driven transport processes. Delta-SWAT water quality trend estimates are compared with water quality monitoring conducted throughout the Delta. Aquatic plant response to water quality and other environmental factors is carried out using a customized model component. Plant response to the range of water quality factors, response times, and altered temperature and light regimes of the Delta have required gap-filling studies to provide model parameters. Delta-SWAT provides a tool for evaluating temporal and spatial effects of land-use and altered environments in the Delta and contributing watersheds on aquatic weed growth. Using Delta-SWAT for simulation modeling allows evaluation of historic and current conditions as well as consideration potential climate change and management practice outcomes. Delta-SWAT adds to the scientific understanding of dynamics in the Delta and enhances development of science-informed, management strategies and practices.

Ecosystem↗
NASA NTRSDate not supplied

Effects of Ambient Alcohol Levels on the Real-time Monitoring of the Atmosphere of the International Space Station

Monitoring of the spacecraft environment is required to ensure the health of the crew and the vehicle systems. For the ISS atmosphere, routine volatile organic compound (VOC) monitoring has been performed for almost a decade by Air Quality Monitors (AQMs). The target compounds measured by the AQMs include three types of chemicals: 1) those compounds that would be harmful to crew, 2) those compounds that have been detected regularly in archival samples, and 3) compounds that, while not necessarily harmful to crew health, could present problems for Environmental Control and Life Support Systems (ECLSS). Following the docking of SpaceX-Demo1 (SpX-DM1), the AQMs began to report high levels of isopropanol (IPA). While elevated IPA is routinely observed with visiting vehicles, the level measured by the AQM, and its continued presence following multiple days of scrubbing, caused concerns regarding the U.S. Water Recovery System. Following the departure of SpX-DM1, the IPA levels decreased to nominal levels, allowing the team to investigate the cause of the elevated measurements. Based on the changes in the shape of the gas chromatograph (GC) traces in the IPA region during docked operations, it appeared that an unknown coeluting species was causing problems with quantification. However, with the docking of Northrup-Grumman-11 (NG-11), the elevated IPA returned, as well as the changes in GC traces. In contrast to the SpX-DM1 results, the AQM IPA results did not return to nominal levels following the departure of NG-11, suggesting that the changes could not be tied directly to the visiting vehicle. In this paper, we will discuss a number of potential causes for both the genuine (measured in archival samples) increases in IPA as well as the much higher levels measured by the AQM. Additionally, we will discuss methods being explored to decrease the potential for a reoccurrence in the future.

William T. Wallace↗
NASA NTRS1973

Instrumentation for air quality measurements.

Comparison of the new generation of air quality monitoring instruments with some more traditional methods. The first generation of air quality measurement instruments, based on the use of oxidant coulometric cells, nitrogen oxide colorimetry, carbon monoxide infrared analyzers, and other types of detectors, is compared with new techniques now coming into wide use in the air monitoring field and involving the use of chemiluminescent reactions, optical absorption detectors, a refinement of the carbon monoxide infrared analyzer, electrochemical cells based on solid electrolytes, and laser detectors.

Loewenstein, M.↗
NASA NTRS1976

Technology transfer potential of an automated water monitoring system

The nature and characteristics of the potential economic need (markets) for a highly integrated water quality monitoring system were investigated. The technological, institutional and marketing factors that would influence the transfer and adoption of an automated system were studied for application to public and private water supply, public and private wastewater treatment and environmental monitoring of rivers and lakes.

Jamieson, W. M.↗
DOE OSTI2022

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

42 ENGINEERING↗
NASA NTRS2022

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

Online anomaly detection↗
NASA NTRSDate not supplied

Impact of Canadian Wildfires on Mid Atlantic’s Region Air Quality: An Analysis Using ASDC Data

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗
NASA NTRSDate not supplied

Analyzing the Impact of Canadian Wildfires on Air Quality in the U.S. Mid-Atlantic: with Data and Tools from NASA’s Atmospheric Sciences Data Center

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗
NASA NTRS1971

Water Pollution Detection by Reflectance Measurements

Measurement of the intensity of light reflected from various planar liquid surfaces has been performed. The results of this brief study show that the presence of a film of foreign material floating on a reference substrate is easily detected by reflectance measurement if the two liquids possess significantly different refractive indices, for example, oil (n = 1.40) and water (n = 1.33). Additional study of various optical configurations, and the building and testing of a prototype monitoring device revealed that the method is sufficiently practical for application to continuous water quality monitoring.

Goolsby, A. D.↗
NASA NTRS1996

Test Structures for Rapid Prototyping of Gas and Pressure Sensors

A multi-project ceramic substrate was used in developing a gas sensor and pressure sensor. The ceramic substrate cantained 36 chips with six variants including sensors, process control monitors, and an interconnect ship. Tha gas sensor is being developed as an air quality monitor and the pressure gauge as a barometer.

ceramics ceramic substrate gas sensor pressure sen↗
NASA NTRS2014

Satellite Monitoring Over the Canadian Oil Sands: Highlights from Aura OMI and TES

Satellite remote sensing provides a unique perspective for air quality monitoring in and around the Canadian Oil Sands as a result of its spatial and temporal coverage. Presented are Aura satellite observations of key pollutants including nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), ammonia (NH3), methanol (CH3OH), and formic acid (HCOOH) over the Canadian Oil Sands. Some of the highlights include: (i) the evolution of NO2 and SO2 from the Ozone Monitoring Instrument (OMI), including comparisons with other nearby sources, (ii) two years of ammonia, carbon monoxide, methanol, and formic acid observations from 240 km North-South Tropospheric Emission Spectrometer (TES) transects through the oils sands, and (iii) preliminary insights into emissions derived from these observations.

NO2↗
NASA NTRSDate not supplied

Effects of Ambient Alcohol Levels on the Real-time Monitoring of the Atmosphere of the International Space Station

Effects of Ambient Alcohol Levels on the Real-time Monitoring of the Atmosphere of the International Space StationWilliam T. Wallace,1 Thomas F. Limero,1 Kenneth W. Clark,2 and Daniel B. Gazda31KBR, 2400 NASA Pkwy., Houston, TX 770582JES Tech, 16870 Royal Crest Dr., Houston, TX 770583NASA Lyndon B. Johnson Space Center, 2101 NASA Pkwy., Houston, TX 77058Monitoring of the spacecraft environment is required to ensure the safety of the crew and the health of the vehicle systems. For the ISS atmosphere, routine monitoring has been performed for many years by the Major Constituent Analyzer (MCA) and two Air Quality Monitors (AQMs), which, together, are used to monitor for trace (ppb) levels of 22 volatile organic compounds (VOCs). The target compounds measured by the AQMs include three types of chemicals: 1) those compounds that would be harmful to crew, 2) those compounds that have been detected regularly in archival samples, and 3) compounds that, while not necessarily harmful to crew health, could present problems for Environmental Control and Life Support Systems (ECLSS).In March 2019, following the docking of SpaceX-Demo1 (SpX-DM1), the on-board AQMs began to report extremely high levels of isopropyl alcohol (IPA). While elevated IPA is not abnormal following the docking of visiting vehicles (due to cleaning of the cargo prior to flight), the level measured by the AQM, and its continued presence following multiple days of scrubbing, caused concerns regarding the U.S. Water Recovery System. Following the departure of SpX-DM1, the IPA levels decreased to nominal levels, allowing the team to investigate the cause of the elevated measurements. Initially, based on the changes in the shape of the gas chromatograph (GC) traces in the IPA region during docked operations, it appeared that some unknown coeluting species was causing problems with quantification. However, with the docking of Northrup-Grumman-11 (NG-11), the elevated IPA concentrations returned, as well as the changes in GC traces. In contrast to the SpX-DM1 results, though, the AQM IPA results did not return to nominal levels following the departure of NG-11, suggesting that the changes could not be tied directly to the visiting vehicle.In this paper, we will discuss a number of potential causes for both the genuine (measured in archival samples) increases in IPA as well as the much higher levels measured by the AQM. Additionally, we will discuss methods being explored to decrease the potential for a reoccurrence in the future.

William T Wallace↗