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DOE OSTI2024

Integrated Off-Gas System Tests on the DM1200 Melter with RPP-WTP LAW Sub-Envelope Bl Simulants, VSL-03R3851-1, Rev. 0 (Oct 2003)

The report documents melter and off-gas performance results obtained on the DM1200 melter during processing of LAW Sub-Envelope B1 feed. The principal objectives of the DM1200 melter testing were to demonstrate suitable processing and production rates for LAW B1 feed; characterize the glass product for elemental composition; measure elemental emission rates and decontamination factors (DFs) across the melter and off-gas treatment components; and provide additional data on the performance of the thermal catalytic oxidation and selective catalytic reduction (TCO/SCR) unit efficiency in treating organic emissions. The feed was spiked with organic compounds for part of the testing duration. All data were collected for use in engineering and system design purposes. No sampling and analysis to collect environmental data was performed during these tests.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2001

Evaluation of Cirrus Cloud Simulations Using ARM Data - Development of a Case Study Data Set

Cloud-resolving models (CRMs) provide an effective linkage in terms of parameters and scales between observations and the parametric treatments of clouds in global climate models (GCMs). They also represent the best understanding of the physical processes acting to determine cloud system lifecycle. The goal of this project is to improve state-of-the-art CRMs used for studies of cirrus clouds and to establish a relative calibration with GCMs through comparisons among CRMs, single column model (SCM) versions of the GCMs, and observations. This project will compare and evaluate a variety of CRMs and SCMs, under the auspices of the GEWEX Cloud Systems Study (GCSS) Working Group on Cirrus Cloud Systems (WG2), using ARM data acquired at the Southern Great Plains (SGP) site. This poster will report on progress in developing a suitable WG2 case study data set based on the September 26, 1996 ARM IOP case - the Hurricane Nora outflow case. The environmental data (input) will be described as well as the wealth of validating cloud observations. We plan to also show results of preliminary simulations. The science questions to be addressed derive significantly from results of the GCSS WG2 cloud model comparison projects, which will be briefly summarized.

O'C.Starr, David↗

DOE OSTI2026

Computational Modeling of Atmospheric Processes at Texas Southern University

Texas Southern University (TSU) is strengthening its research program in atmospheric chemistry and physics with a climate science emphasis by leveraging partnerships with the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Facility, Brookhaven National Laboratory (BNL), and the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This RDPP-supported program focuses on secondary organic aerosols (SOAs) and reactive atmospheric species that influence cloud formation, precipitation processes, and radiative forcing. SOAs play a critical role in cloud microphysics and Earth’s energy balance, yet the chemical and physical mechanisms governing SOA–cloud interactions remain a significant source of uncertainty in predictive climate models. Through computational modeling, observational data analysis, and national laboratory collaboration, this program develops a skilled cohort of students trained in atmospheric science, environmental data analysis, and climate-relevant modeling. These research experiences build technical competencies that are transferable to careers in government laboratories, academia, and industry. By engaging students from historically underrepresented communities in high-impact climate research, TSU expands participation in the atmospheric sciences workforce while contributing meaningful scientific insights to DOE-supported ARM research activities. This partnership strengthens national capacity in climate science and supports the development of the next generation of atmospheric researchers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

An Investigation on the Pollen-Induced Soiling Losses in Utility-Scale PV Plants

Soiling, the accumulation of dust and other contaminants on the surface of photovoltaic (PV) modules, is a common factor that can negatively impact the performance of PV systems. In this study, the authors aim to analyze the impact of pollen on soiling losses in PV systems located in North Carolina, USA, particularly during the spring season. The performance data of two utility-scale PV plants was collected and analyzed using the two soiling extraction methods. Environmental data, including croplands and vegetation was also collected and analyzed to identify correlations with soiling losses. The results of the study may help improve understanding of necessary operation and maintenance activities for PV plants and provide new insights into the phenomenon of pollen deposition on PV systems.

correlation↗

NASA NTRS2007

NASA's NPOESS Preparatory Project Science Data Segment: A Framework for Measurement-based Earth Science Data Systems

The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) provides a framework for the future of NASA s distributed Earth science data systems. The NPP SDS performs research and data product assessment while using a fully distributed architecture. The components of this architecture are organized around key environmental data disciplines: land, ocean, ozone, atmospheric sounding, and atmospheric composition. The SDS thus establishes a set of concepts and a working prototypes. This paper describes the framework used by the NPP Project as it enabled Measurement-Based Earth Science Data Systems for the assessment of NPP products.

Schwaller, Mathew R.↗

NASA NTRS2019

An Inter-Comparison Exercise of Sentinel-2 Radiometric Validations Assessed by Independent Expert Groups

Copernicus is the European Union's Earth Observation and Monitoring programme, delivering free access to operational and historical environmental data to support applications in a wide range of societal benefit areas. To allow meaningful long-term environmental monitoring and robust decision-making, it is essential to ensure that satellite-retrieved products are of high quality and consistency. This paper describes the outputs of an international workshop on the radiometric calibration validation of the Copernicus Sentinel-2A and Sentinel-2B Multi-Spectral Instrument. A wide range of vicarious methodologies have been applied independently and then compared per type of target. All methods agree on the good radiometric performance of both Sentinel-2A and Sentinel-2B with respect to the mission requirements as well as on evidence of a slight bias between the two instruments. Comparisons of all these results are discussed to highlight the benefits and advantages of the methods as well as to propose potential improvements either for the methods themselves and/or for the comparison exercise.

Sentinel-2↗

NASA NTRSDate not supplied

Jpss-4 VIIRS Polarization Sensitivity Performance Comparison With Heritage VIIRS Sensors

The Joint Polar Satellite System 4 (JPSS-4) is the follow-on for the Suomi-National Polar-orbiting Partnership (S-NPP) and Joint Polar Satellite Systems 1-3 (JPSS-1, -2 and -3) missions. A primary sensor on both JPSS and S-NPP spacecrafts is the Visible-Infrared Imaging Radiometer Suite (VIIRS) that provides valuable weather and climate products to the user community. VIIRS covers the Reflective Solar Band (RSB) and Thermal Emissive Band (TEB) spectral regions and contains a Day Night Band (DNB) that uses Lunar illumination at night. VIIRS provides top-of-atmosphere radiance, reflectance, and brightness temperature within the Sensor Data Records (SDRs) that are used in sea surface temperature, cloud characterization, land surface properties and ocean color/chlorophyll Environmental Data Record (EDR) products. The SDR calibration is performed using unpolarized sources such as a Solar Diffuser (SD) for the RSBs or an On-Board Calibrator BlackBody (OBCBB) for the TEBs. Earth scenes with polarizing properties will create radiometric bias errors within the SDRs based on how sensitive VIIRS is to polarized illumination and must be corrected in some EDR algorithms. This paper will discuss the JPSS-4 VIIRS polarization characterization methodology, polarization sensitivity results and compare its performance to its predecessors S-NPP and JPSS-1 through -3 VIIRS.

David Moyer↗

NASA NTRS2015

First SNPP Cal/Val Campaign: Satellite and Aircraft Sounding Retrieval Intercomparison

Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (SNPP) satellite Environmental Data Record (EDR) is retrieved from calibrated ultraspectral radiance so called Sensor Data Record (SDR). It is critical to understand the accuracy of retrieved EDRs, which mainly depends on SDR accuracy (e.g., instrument random noise and absolute accuracy), an ill-posed retrieval system, and radiative transfer model errors. There are few approaches to validate EDR products, e.g., some common methods are to rely on radiosonde measurements, ground-based measurements, and dedicated aircraft campaign providing in-situ measurements of atmosphere and/or employing similar ultraspectral interferometer sounders. Ultraspectral interferometer sounder aboard aircraft measures SDR to retrieve EDR, which is often used to validate satellite measurements of SDR and EDR. The SNPP Calibration/Validation Campaign was conducted during May 2013. The NASA high-altitude aircraft ER-2 that carried ultraspectral interferometer sounders such as the NASA Atmospheric Sounder Testbed-Interferometer (NAST-I) flew under the SNPP satellite that carries the Cross-track Infrared Sounder (CrIS). Here we inter-compare the EDRs produced with different retrieval algorithms from SDRs measured by the sensors from satellite and aircraft. The available dropsonde and radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis were also used to draw the conclusion from this experiment.

Zhou, Daniel K.↗

NASA NTRS1989

Pressure Distribution and Air Data System for the Aeroassist Flight Experiment

The Aeroassist Flight Experiment (AFE) is designed to provide critical flight data necessary for the design of future Aeroassist Space Transfer Vehicles (ASTV). This flight experiment will provide aerodynamic, aerothermodynamic, and environmental data for verification of experimental and computational flow field techniques. The Pressure Distribution and Air Data System (PD/ADS), one of the measurement systems incorporated into the AFE spacecraft, is designed to provide accurate pressure measurements on the windward surface of the vehicle. These measurements will be used to determine the pressure distribution and air data parameters (angle of attack, angle of sideslip, and free-stream dynamic pressure) encountered by the blunt-bodied vehicle over an altitude range of 76.2 km to 94.5 km. Design and development data are presented and include: measurement requirements, measurement heritage, theoretical studies to define the vehicle environment, flush-mounted orifice configuration, pressure transducer selection and performance evaluation data, and pressure tubing response analysis.

Gibson, Lorelei S.↗

NASA NTRS2002

Remote Sensing Information Science Research

This document is the final report summarizing research conducted by the Remote Sensing Research Unit, Department of Geography, University of California, Santa Barbara under National Aeronautics and Space Administration Research Grant NAG5-10457. This document describes work performed during the period of 1 March 2001 thorough 30 September 2002. This report includes a survey of research proposed and performed within RSRU and the UCSB Geography Department during the past 25 years. A broad suite of RSRU research conducted under NAG5-10457 is also described under themes of Applied Research Activities and Information Science Research. This research includes: 1. NASA ESA Research Grant Performance Metrics Reporting. 2. Global Data Set Thematic Accuracy Analysis. 3. ISCGM/Global Map Project Support. 4. Cooperative International Activities. 5. User Model Study of Global Environmental Data Sets. 6. Global Spatial Data Infrastructure. 7. CIESIN Collaboration. 8. On the Value of Coordinating Landsat Operations. 10. The California Marine Protected Areas Database: Compilation and Accuracy Issues. 11. Assessing Landslide Hazard Over a 130-Year Period for La Conchita, California Remote Sensing and Spatial Metrics for Applied Urban Area Analysis, including: (1) IKONOS Data Processing for Urban Analysis. (2) Image Segmentation and Object Oriented Classification. (3) Spectral Properties of Urban Materials. (4) Spatial Scale in Urban Mapping. (5) Variable Scale Spatial and Temporal Urban Growth Signatures. (6) Interpretation and Verification of SLEUTH Modeling Results. (7) Spatial Land Cover Pattern Analysis for Representing Urban Land Use and Socioeconomic Structures. 12. Colorado River Flood Plain Remote Sensing Study Support. 13. African Rainfall Modeling and Assessment. 14. Remote Sensing and GIS Integration.

Clarke, Keith C.↗

NASA NTRS2021

NOAA-20 VIIRS on-Orbit Calibration Improvements

The NOAA-20 (N-20) VIIRS has successfully operated for more than two years since its launch in November 2017. Shortly after completing its initial instrument check-outs and post-launch testing (PLT) activities, the N-20 VIIRS sensor data records (SDR) achieved the beta, provisional, and validated maturity status in January, February, and April 2018, respectively. In this paper, we briefly describe the instrument on-orbit operation and calibration activities, provide an overall assessment of its on-orbit performance, and discuss the methodologies developed to maintain and improve sensor calibration and data quality. As illustrated in this paper, the N-20 VIIRS continues to perform with excellent stability, allowing high-quality environmental data records (EDR) to be generated from its well-calibrated SDR.

NOAA-20↗

DOE OSTI2021

ORT: a workflow linking genome-scale metabolic models with reactive transport codes

Abstract Motivation Nutrient and contaminant behavior in the subsurface are governed by multiple coupled hydrobiogeochemical processes which occur across different temporal and spatial scales. Accurate description of macroscopic system behavior requires accounting for the effects of microscopic and especially microbial processes. Microbial processes mediate precipitation and dissolution and change aqueous geochemistry, all of which impacts macroscopic system behavior. As ‘omics data describing microbial processes is increasingly affordable and available, novel methods for using this data quickly and effectively for improved ecosystem models are needed. Results We propose a workflow (‘Omics to Reactive Transport—ORT) for utilizing metagenomic and environmental data to describe the effect of microbiological processes in macroscopic reactive transport models. This workflow utilizes and couples two open-source software packages: KBase (a software platform for systems biology) and PFLOTRAN (a reactive transport modeling code). We describe the architecture of ORT and demonstrate an implementation using metagenomic and geochemical data from a river system. Our demonstration uses microbiological drivers of nitrification and denitrification to predict nitrogen cycling patterns which agree with those provided with generalized stoichiometries. While our example uses data from a single measurement, our workflow can be applied to spatiotemporal metagenomic datasets to allow for iterative coupling between KBase and PFLOTRAN. Availability and implementation Interactive models available at https://pflotranmodeling.paf.subsurfaceinsights.com/pflotran-simple-model/. Microbiological data available at NCBI via BioProject ID PRJNA576070. ORT Python code available at https://github.com/subsurfaceinsights/ort-kbase-to-pflotran. KBase narrative available at https://narrative.kbase.us/narrative/71260 or static narrative (no login required) at https://kbase.us/n/71260/258. Supplementary information Supplementary data are available at Bioinformatics online.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1990

Meteorological Instruction Software

At Florida State University and the Naval Postgraduate School, meteorology students have the opportunity to apply theoretical studies to current weather phenomena, even prepare forecasts and see how their predictions stand up utilizing GEMPAK. GEMPAK can display data quickly in both conventional and non-traditional ways, allowing students to view multiple perspectives of the complex three-dimensional atmospheric structure. With GEMPAK, mathematical equations come alive as students do homework and laboratory assignments on the weather events happening around them. Since GEMPAK provides data on a 'today' basis, each homework assignment is new. At the Naval Postgraduate School, students are now using electronically-managed environmental data in the classroom. The School's Departments of Meteorology and Oceanography have developed the Interactive Digital Environment Analysis (IDEA) Laboratory. GEMPAK is the IDEA Lab's general purpose display package; the IDEA image processing package is a modified version of NASA's Device Management System. Bringing the graphic and image processing packages together is NASA's product, the Transportable Application Executive (TAE).

Source record↗

NASA NTRS2002

Ocean Color Data at the Goddard Earth Sciences (GES) DAAC: CZCS, SeaWiFS, OCTS, MODIS-Terra, MODIS-Aqua

The Goddard Earth Sciences Distributed Active Archive Center (DAAC) is the designated archive for all of the ocean color data produced by NASA satellite missions. The DAAC is a long-term, high volume, secure repository for many different kinds of environmental data. With respect to ocean color, the Goddard DAAC holds all the data obtained during the eight-year mission of the Coastal Zone Color Scanner (CZCS). The DAAC is currently receiving data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and the MODIS-Terra instrument. The DAAC recently received reformatted data from the Ocean Color and Temperature Scanner (OCTS) and will also archive MODIS-Aqua Ocean products. In addition to its archive and distribution services, the Goddard DAAC strives to improve data access, ease-of-use, and data applicability for a broad spectrum of customers. The DAAC's data support teams practice dual roles, both insuring the integrity of the DAAC data archive and serving the user community with answers to user inquiries, online and print documentation, and customized data services.

Source record↗

NASA NTRS2007

Evaluation of Integrating the Invasive Species Forecasting System to Support National Park Service Decisions on Fire Management Activities and Invasive Plant Species Control

The USGS and NASA, in conjunction with Colorado State University, George Mason University and other partners, have developed the Invasive Species Forecasting System (ISFS), a flexible tool that capitalizes on NASA's remote sensing resource to produce dynamic habitat maps of invasive terrestrial plant species across the United States. In 2006 ISFS was adopted to generate predictive invasive habitat maps to benefit noxious plant and fire management teams in three major National Park systems: The Greater Yellowstone Area (Yellowstone / Grand Tetons National Parks), Sequoia and Kings Canyon National Park, and interior Alaskan (between Denali, Gates of The Arctic and Yukon-Charley). One of the objectives of this study is to explore how the ISFS enhances decision support apparatus in use by National Park management teams. The first step with each park system was to work closely with park managers to select top-priority invasive species. Specific species were chosen for each study area based on management priorities, availability of observational data, and their potential for invasion after fire disturbances. Once focal species were selected, sources of presence/absence data were collected from previous surveys for each species in and around the Parks. Using logistic regression to couple presence/absence points with environmental data layers, the first round of ISFS habitat suitability maps were generated for each National Park system and presented during park visits over the summer of 2006. This first engagement provided a demonstration of what the park service can expect from ISFS and initiated the ongoing dialog on how the parks can best utilized the system to enhance their decisions related to invasive species control. During the park visits it was discovered that separate "expert opinion" maps would provide a valuable baseline to compare against the ISFS model output. Opinion maps are a means of spatially representing qualitative knowledge into a quantitative two-dimensional map. Furthermore, our approach combines the qualitative expert opinion habitat maps -- with the quantitative ISFS habitat maps in a difference map that shows where the two maps agree and disagree. The objective of the difference map is to help focus future field sampling and improve model results. This paper presents a demonstration of the habitat, expert opinion, and difference map for Yellowstone National Park.

Ma, Peter↗

NASA NTRSDate not supplied

Next-generation wildlife tracking devices and integrated sensors for measuring species-environment interactions and advancing conservation

Global land use and climate change have magnified the importance of collecting accurate animal movement and environmental data to improve our ability to model species interactions with the environment and promote effective conservation. Advanced animal tracking devices that couple cutting-edge technologies with our expanding need for ecological information is critical. In addition to further optimizing device size to monitor small, sensitive species, new paradigms for collecting, storing, and transmitting data about animals and their environments will propel wildlife tracking devices forward. Advanced telemetry capabilities will increase our ability to pair location and sensor data from tagged wildlife with remote sensing data. The USGS Western Ecological Research Center, NASA Ames Research Center, and collaborators have been developing new wildlife tracking devices and integrated environmental sensors to address these challenges. We describe a new, miniaturized solar GPS-enabled Globalstar satellite transmitter with accelerometer capability that is 20% lighter and 25% less expensive than existing commercially available tags. We also introduce a novel peer-to-peer, solar-powered network tag that uses long-range, low-power, wireless platform technology. Concurrently, we began adapting a carbon nanotube (CNT) sensor to detect dimethyl sulfide (DMS), a trace gas relevant to marine ecology and climate studies. CNT sensors offer a small, lightweight, and low-power technology that can detect changes in resistance across carbon nanotubes coated with adsorbent selected to specifically bind with a variety of reactive trace gasses. We flew a prototype sensor in a small UAS and sampled an apparent increase in DMS concentration consistent with a well-defined marine frontal boundary. Currently we are integrating project components to create a hybridized architecture of networked peer-to-peer and satellite tags with integrated CNT and additional on-board and remote sensors to advance animal tracking and to provide information for next generation wildlife conservation.

Ian G. Brosnan↗

NASA NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks and challenges associated with deep space missions and experiments (cis-Lunar, Mars transit/surface) require new knowledge discovery and development of novel ecosystems. Supporting distant and long-duration missions and experiments requires biological data (from yeast, microbes, fruit flies, C. elegans, plants, crops, rodents, humans) be findable, accessible, interoperable, reusable (FAIR), and maximally open-access. As data-intensive, bioinformatic, meta-analytical, and computer-assisted approaches continue to be a centerpiece of modern research, the NASA Biological and Physical Sciences division is expanding its Open Science capabilities beyond NASA GeneLab. The NASA Ames Life Sciences Data Archive (ALSDA) is a repository which is responsible for collecting and access to space biological imagery and video, alongside tabular and environmental data. In this presentation, we will discuss strategies dealing with archiving, curating, and accessibility of images from very distinct imaging modalities (e.g., micro-computed tomography, magnetic resonance imaging, photographic images of plants, fluorescence microscopy, behavioral videos, etc.). There are two main challenges: 1. Open-source data storage and 2. Metadata related to the imagery-video. Both have been solved by leveraging two existing open-source systems. For data storage, ALSDA is utilizing components through the Open Microscopy Environment (OME), which can read most imaging proprietary formats and display on a web interface complex multidimensional images (Z stack, multi-channel, temporal, spectral). Most technical metadata from imaging modalities are captured seamlessly. For metadata capturing experimental details, ALSDA (like GeneLab) uses the ISA-Tab specification which relies on the ISA data model to order and classify metadata. The ISA data model uses a tree structure with three files to capture the metadata: The top layer is the Investigations file, the second layer is the Study file(s), and the last layer is the Assay file(s). We believe such an approach may be useful for other types of image research data from other investigators in the AGU community.

imaging↗

DOE OSTI2023

An Investigation on the Pollen-Induced Soiling Losses in Utility-Scale PV Plants

Here in this study, the impact of pollen as a PV soiling agent is investigated. The performance data of five utility-scale PV plants in North Carolina, USA, was collected and analyzed using two soiling extraction methods. Satellite and environmental data, including pollen counts, cropland, and vegetation, was also collected and analyzed to identify impacts to soiling losses. During the spring peak pollen season, performance losses of >15% were observed at all five sites. Partial performance recoveries following the pollen season were slow, with lack of correlation with rainfall. This means that the statistical soiling estimation methods that assume abrupt performance recovery from rain are not appropriate for pollen-impacted solar sites. When manual cleanings were performed on site the performance recovery ranged from 5% to 11% indicating persistent soiling impacts are present in this region. The results of this work provide new insights into the phenomenon of pollen deposition on PV systems, demonstrating that 1) soiling can also affect systems located in rainy locations and 2) that its effects cannot be determined using the current estimation methodologies.

14 SOLAR ENERGY↗