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At least 721 records · Page 40

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DOE OSTI2021

Assessing the life-cycle environmental impacts of the wood pallet sector in the United States

Wood pallets play a critical role in the movement and storage of goods worldwide. They are an important component in the complex global supply chain and used by almost every industry. It is therefore important to assess the environmental implications of the wood pallet supply chain and identify optimization strategies that can be implemented. In this paper, primary 2018 annual production data collected from U.S. pallet manufacturers were used to develop the first industry-average life-cycle inventory (LCI). A new functional unit was proposed to perform a more refined and accurate environmental life-cycle assessment of the wood pallet supply chain. Using the LCI data developed, a cradle-to-grave industry-average life-cycle impact assessment was performed. This novel approach quantifies environmental impacts of a generic multi-use pallet, including repair and remanufacturing. The total global warming impact was 10.4 kg CO 2 e per 45.4 t of pallet loads of product delivered using wood pallets. The manufacturing stage contributed the most, about 35%, followed by the raw material supply stage. About 41% of total primary energy consumption was from renewable sources, with most sourced from biomass. Fossil fuels comprised about 52% of the total (225 MJ per functional unit) primary energy consumption. Total environmental impact was significantly affected by two main parameters: reference service life and load-bearing capacity. Pallet repair was also found to be an important component of the wood pallet supply chain, which has a low environmental footprint compared with the overall impact of a pallet and enables mitigation of overall impact by extending the reference service life. Finally, at end-of-life, common industry practices demonstrated substantial potential environmental benefits that can minimize overall environmental impact.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1974

Application of ERTS-1 satellite imagery for land use mapping and resource inventories in the central coastal region of California

ERTS-1 satellite imagery has proved a valuable data source for land use as well as natural and cultural resource studies on a regional basis. ERTS-1 data also provide an excellent base for mapping resource related features and phenomena. These investigations are focused on a number of potential applications which are already showing promise of having operational utility.

Estes, J. E.↗

NASA NTRS1975

Environmental monitoring from spacecraft data

The author has identified the following significant results. LANDSAT was used as a basis for inventorying land use within each of the Ohio-Kentucky-Indiana regional commissions, 225 drainage areas, and nine counties. Computer tabulations were produced to obtain the area covered by each of 16 land use categories within 225 drainage areas. The 16 categories were merged into ten categories and mapped at a scale of 1 inch = 5,000 ft, with detail to 0.44 hectares for the 2,700 sq mi region. These products were produced in less than 90 days, at a cost of $20,000.

Rogers, R. H.↗

NASA NTRS1977

Application of LANDSAT system for improving methodology for inventory and classification of wetlands

The author has identified the following significant results. LANDSAT and aircraft data were compared for differences in absolute numbers of water bodies in the two data sets. This comparison was done using a linear regression analysis. The coefficients of determination were 0.65 and 0.74 for data of May and July, respectively. Standard statistical procedures were used to adjust the LANDSAT pond counts to actual pond numbers based on regression relationships.

Gilmer, D. S.↗

NASA NTRS1981

Resource inventory techniques used in the California Desert Conservation Area

A variety of conventional and remotely sensed data for the 25 million acre California Desert Conservation Area (CDCA) have been integrated and analyzed to estimate range carrying capacity. Multispectral classification was performed on a digital mosaic of ten Landsat frames. Multispectral classes were correlated with low level aerial photography, quantified and aggregated by grazing allotment, land ownership, and slope.

Mcleod, R. G.↗

NASA NTRS2021

Mangrove Carbon Stocks in Pongara National Park, Gabon

Mangroves are recognized for their valued ecosystem services to coastal areas, and the functional linkages between those services and ecosystem carbon stocks have been established. However, spatially explicit inventories are necessary to facilitate management and protection of mangroves, as well as providing a foundation for payment for ecosystem service programs such as REDD+. We conducted an inventory of carbon stocks in mangroves within Pongara National Park (PNP), Gabon using a stratified random sampling design based on forest canopy height derived from TanDEM-X remote sensing data. Ecosystem carbon pools, including aboveground and belowground biomass and necromass, and soil carbon to a depth of 2 m were assessed using measurements and samples from plots distributed among three canopy height classes within the park. There were two mangrove species within the inventory area in PNP, Rhizophora racemosa and R. harrisonii. R. harrisonii was predominant in the sparse, low-stature stands that dominated the west side of the park. In the east side of the park, both species occurred in tall-stature stands, with tree height often exceeding 30 m. Canopy height was an effective means to stratify the inventory area, as biomass was significantly different among the height classes. Despite those differences in aboveground biomass, the soil carbon density was not significantly different among height classes. Soils were the main component of the ecosystem carbon stock, accounting for over 84% of the total. The ecosystem carbon density ranged from 644 to 943 Mg C ha−1 among the three height classes. The ecosystem carbon stock within PNP is estimated to be 40,588 Gg C. The combination of pre-inventory information about stand conditions and their spatial distribution within the assessment area obtained from remote sensing data and a spatial decision support system were fundamental to implementing this relatively large-scale field inventory. This work exemplifies how mangrove carbon stocks can be quantified to augment national C reporting statistics, provide a baseline for projects involving monitoring, reporting and verification (i.e., MRV), and provide data on the forest composition and structure for sustainable management and conservation practices.

Carl C Trettin↗

NASA NTRS2012

Derivation of a New Smoke Emissions Inventory using Remote Sensing, and Its Implications for Near Real-Time Air Quality Applications

A new emissions inventory of particulate matter (PM) is being derived mainly from remote sensing data using fire radiative power (FRP) and aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, as well as wind data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis dataset, which spans the satellite era. This product is generated using a coefficient of emission, C(sub e), that has been produced on a 1x1 degree global grid such that, when it is multiplied with satellite measurements of FRP or its time-integrated equivalent fire radiative energy (FRE) retrieved over a given area and time period, the corresponding PM emissions are estimated. This methodology of using C(sub e) to derive PM emissions is relatively new and advantageous for near real-time air quality applications compared to current methods based on post-fire burned area that may not provide emissions in a timely manner. Furthermore, by using FRP to characterize a fire s output, it will represent better accuracy than the use of raw fire pixel counts, since fires in individual pixels can differ in size and strength by orders of magnitude, resulting in similar differences in emission rates. Here we will show examples of this effect and how this new emission inventory can properly account for the differing emission rates from fires of varying strengths. We also describe the characteristics of the new emissions inventory, and propose the process chain of incorporating it into models for air quality applications.

Ellison, Luke↗

DOE OSTI2022

NGEE Arctic Soil Pit and Core Inventory for Samples Collected Between 2016-2019: Locations, Sampling Characteristics, Collection, and Contacts, Seward Peninsula, Alaska, USA

This dataset includes associated information about individual pit and core samples (e.g., location, contact, date, data collected) sampled between 2016 and 2019 from NGEE Arctic sites at Teller (MM 27 and MM47), Kougarok (MM47 and MM56, Hillslope, and vegetation plot areas), and Council (MM71). The inventory is qualitative and excludes those datasets on soil pit cores that included time-series information. The package includes one each *.csv data file, *.kml and *.pdf. All quantitative data is available in the related datasets https://doi.org/10.5440/1417652, https://doi.org/10.5440/1423892, https://doi.org/10.5440/1342956, https://doi.org/10.5440/1854940, https://doi.org/10.5440/1544760, https://doi.org/10.5440/1346200, and https://doi.org/10.5440/1856042. The goal of this dataset is to help modelers understand when, where, and what data was collected with respect to physical soil properties on the Seward Peninsula, AK, USA over the course of NGEE Arctic’s campaigns in the region from 2016-2019. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort 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 OSTI2025

Tracking cropland transitions: A comparative analysis of U.S. land cover change data

There are a growing number of land cover data available for the conterminous United States, supporting various applications ranging from biofuel regulatory decisions to habitat conservation assessments. These datasets vary in their source information, frequency of data collection and reporting, land class definitions, categorical detail, and spatial scale and time intervals of representation. These differences limit direct comparison, contribute to disagreements among studies, confuse stakeholders, and hamper our ability to confidently report key land cover trends in the U.S. Here we assess changes in cropland derived from the Land Change Monitoring, Assessment, and Projection (LCMAP) dataset from the U.S. Geological Survey and compare them with analyses of three established land cover datasets across the coterminous U.S. from 2008-2017: (1) the National Resources Inventory (NRI), (2) a dataset Lark et al. 2020 derived from the Cropland Data Layer (CDL), and (3) a dataset from Potapov et al. 2022. LCMAP reports more stable cropland and less stable noncropland in all comparisons, likely due to its more expansive definition of cropland which includes managed grasslands (pasture and hay). Despite these differences, net cropland expansion from all four datasets was comparable (5.18-6.33 million acres), although the geographic extent and type of conversion differed. LCMAP projected the largest cropland expansion in the southern Great Plains, whereas other datasets projected the largest expansion in the northwestern and central Midwest. Most of the pixel-level disagreements (86%) between LCMAP and Lark et al. 2020 were due to definitional differences among datasets, whereas the remainder (14%) were from a variety of causes. Cropland expansion in the LCMAP likely reflects conversions of more natural areas, whereas cropland expansion in other data sources also captures conversion of managed pasture to cropland. The particular research question considered (e.g., habitat versus soil carbon) should influence which data source is more appropriate.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1975

Single-class classification

Often, when classifying multispectral data, only one class or crop is of interest, such as wheat in the Large Area Crop Inventory Experiment (LACIE). Usual procedures for designing a Bayes classifier require that labeled training samples and therefore ground truth be available for the 'class of interest' plus all confusion classes defined by the multispectral data. This paper will consider the problem of designing a two-class Bayes classifier which will classify data into the 'class of interest' or the 'other' classes but will require only labeled training samples from the 'class of interest' to design the classifier. Thus, this classifier minimizes the need for ground truth. For these reasons, the classifier is referred to as a single-class classifier. A procedure for evaluating the overall performance of the single-class classifier in terms of the probability of error will be discussed.

Minter, T. C.↗

DOE OSTI2023

Hydropower Resilience Database for Assessing Microgrid Formation Capability and Enhancing Power Grid Resilience

In the face of increasing frequency of extreme events, enhancing resilience and reliability of energy infrastructure demands innovative solutions. Hydropower, with its inherent generation flexibility and grid-forming capability, offers significant potential for enhancing power grid resilience through the establishment of microgrids. To enable informed decision-making and strategic planning, we present the Hydropower Resilience Database (HRD) that integrates data from various sources such as Oakridge National Laboratory (ORNL) HydroSource, National Inventory of Dams, and US Western Grid database. By integrating relevant information on hydropower plant characteristics, including dams, reservoirs, and connected electrical grid, this resource enables hydropower plant owners, utilities, and community stakeholders to identify and evaluate the feasibility of using hydropower resources in microgrids to support nearby communities and critical infrastructure in various challenging scenarios. Using HRD, a set of metrics are evaluated to quantify the capability of hydropower plants to support essential microgrid functions. An interactive tool is developed using ArcGIS, enabling the visualization and analysis using HRD. Our research contributes to strategic planning efforts for fortifying energy infrastructure, ensuring reliable power supply during disruptions, and advancing the development of robust and resilient energy systems in regions susceptible to grid vulnerabilities.

13 HYDRO ENERGY↗

DOE OSTI2023

Hydropower Resilience Database for Assessing Microgrid Formation Capability and Enhancing Power Grid Resilience

13 HYDRO ENERGY↗

NASA NTRS1981

AgRISTARS - Plans and first-year achievements

The results of the agriculture and resources inventory surveys through aerospace remote sensing (AgRISTARS) program managed by the USDA for exploring the use of satellite data for domestic and global commodity information needs are discussed. The program was intended to gather early warning of changes affecting production and quality of commodities and renewable resources, for predicting commodity production, land use classification and quantification, for inventories and assessments of renewable resources, land productivity measurements, assessment of conservation practices, and for pollution detection and impact evaluation. Up to 20 crop/region combinations in 7 countries were covered by the experiments, which comprised NOAA 6 and Landsat data analyses. Attempts to reduce variances through improved machine classification techniques are reported, together with soil moisture profiling, and the use of airborne sensors for providing comparative data.

Hall, F. G.↗

NASA NTRS1975

Coal refuse site inventories

Small-scale color-infrared aerial photography at 1:120,000 scale is used to carry out an operational survey of coal refuse sites. Site analyses and reclamation cost estimates are completed in less than 90 days by using remote sensing techniques. Analysis of photographs provided dependable and accurate data for the location and environmental assessment of nearly 200 coal refuse banks and slurry ponds. The inventory constitutes a comprehensive reference for establishing priorities for coal refuse site reclamation and for complementing future field surveys.

Wobber, F. J.↗

NASA NTRS2010

Estimates of the Lightning NOx Profile in the Vicinity of the North Alabama Lightning Mapping Array

The NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) is applied to August 2006 North Alabama Lightning Mapping Array (LMA) data to estimate the raw (i.e., unmixed and otherwise environmentally unmodified) vertical profile of lightning nitrogen oxides, NOx = NO + NO 2 . This is part of a larger effort aimed at building a more realistic lightning NOx emissions inventory for use by the U.S. Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) modeling system. Data from the National Lightning Detection Network TM (NLDN) is also employed. Overall, special attention is given to several important lightning variables including: the frequency and geographical distribution of lightning in the vicinity of the LMA network, lightning type (ground or cloud flash), lightning channel length, channel altitude, channel peak current, and the number of strokes per flash. Laboratory spark chamber results from the literature are used to convert 1-meter channel segments (that are located at a particular known altitude; i.e., air density) to NOx concentration. The resulting raw NOx profiles are discussed.

Koshak, William J.↗

DOE OSTI2026

Rapid Analyses of Sparse Seismoacoustic Data Reveals the Timing and Size of the Accurate Energetic Systems Explosion

On 10 October 2025 an explosion occurred at a facility operated by Accurate Energetic Systems in Humphreys County, Tennessee. The incident resulted in 16 fatalities and created a debris field over several square kilometers. To address remaining questions about explosion timing and size, we collected about 20 seismic and 19 acoustic records of the blast from sensors up to hundreds of kilometers away. We then deployed 10 distinct physics-based, reduced order models (ROMs) that used validated geological structure and atmospheric conditions from the time of the event, along with observations of body- and surface-wave energy, as well as acoustic overpressure and phase duration. Each ROM predicted either timing, yield estimates, or both. We binned these estimates and their uncertainties according to each ROMs’ assumptions about confinement (aboveground, buried fully coupled, and buried partially coupled) and combined these estimates with other forensic data to conclude that the event occurred as a single, aboveground explosion on 10 December 2025 12:47:50.8 ±0.1 s with a yield equivalent to 11.8 [2.3,16.5] tons of Trinitrotoluene. Our estimates align with the Bureau of Alcohol, Tobacco, Firearms and Explosives inventory reports of 11–13 tons. This multimethod approach demonstrates the use of remotely observed geophysical data to rapidly aid conventional forensic investigations of accidental explosions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2023

Review and Summary of Oxide Thickness Data for Aluminum-Clad Spent Nuclear Fuel

The U.S. Department of Energy (DOE) owns a large inventory of aluminum-clad spent nuclear fuel (ASNF) in interim storage pending ultimate disposition, with more being generated by currently operating research reactors. Dry storage in sealed DOE Standard Canisters is being investigated as an approach for long-term interim storage and/or disposition in a repository for ASNF. A primary challenge for ASNF storage is the presence of aluminum (oxy)hydroxide layers formed on the cladding surfaces during water exposure in the reactor and in wet storage, which forms a reservoir of chemisorbed water not readily removed at low (<100°C) drying temperatures. Free, physisorbed, and chemisorbed water are all susceptible to radiolytic breakdown under irradiation and can release hydrogen gas. Identifying the likely range of (oxy)hydroxide loadings on ASNF that may be placed in dry storage will help to ensure that the impact of the (oxy)hydroxide is adequately accounted for while avoiding over conservatism and enable mitigation strategies to be implemented where needed. The current report summarizes information on (oxy)hydroxide thicknesses and characteristics from the literature and from recent measurements taken in the present research campaign. In general, corrosion studies have indicated that the corrosion and oxide buildup on aluminum are affected by numerous conditions, including pH, temperature and heat flux, coolant flowrates, irradiation (in-reactor vs. unirradiated tests), duration of water exposure, and the amount of oxide already on the surface. Some of these factors are interrelated (e.g., the local temperature, heat flux, and coolant flowrate). Observations of the impact of irradiation (in-reactor versus ex-reactor measurements) on corrosion and oxide thickness are mixed, but multiple studies indicate that there is a significant difference between in-reactor and ex-reactor corrosion kinetics, even when other operating conditions such as pH, flowrate, heat flux, etc., simulate those in a reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1971

Remote sensing for mined area reclamation: Application inventory

Applications of aerial remote sensing to coal mined area reclamation are documented, and information concerning available data banks for coal producing areas in the east and midwest is given. A summary of mined area information requirements to which remote sensing methods might contribute is included.

Source record↗