SEARCH · Engineering Papers

Results for “Inventory Difference”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Causes of Model Biases in Simulating Inorganic Aerosol Composition During KORUS-AQ and Implications for the Estimate of Transboundary Pollution

East Asia is a region of increasing economic growth which has led to severe PM2.5 pollution in urban areas. The joint NASA-NIER Korea-United States Air Quality (KORUS-AQ) field campaign in May-June 2016 provided an extensive dataset of ground, airborne, and remote sensing observations to test model simulations of PM2.5 pollution transport and potential control measures. During KORUS-AQ, a period of haze was observed in which PM2.5 rapidly increased to the highest levels observed during the campaign. This increase is associated with increasing inorganic aerosol. While a portion of this increase is due to long-range transport, there is observational evidence that aerosol formation from local precursors was also enhanced. This suggests that domestic policy measures could have a greater than expected influence on controlling PM2.5. However, models have difficulty reproducing PM2.5 levels, particularly the composition of secondary inorganic aerosol. Models generally underestimate sulfate and overestimate nitrate and fail to represent the peak levels of PM2.5 during haze events. These biases have been chiefly attributed to errors in chemical mechanisms and model meteorology, not issues with underlying emissions inventories. Here, we use observations from KORUS-AQ interpreted by the GEOS-Chem chemical transport model to improve the model’s ability to reproduce secondary inorganic aerosol concentrations during the campaign and explore mechanisms to improve model biases during the haze event. We assess the fraction of inorganic aerosol from the improved model simulation that results from transboundary transport during KORUS-AQ and test the model sensitivity to potential emission reduction measures that could improve air quality in Seoul during different meteorological periods including haze episodes.

Katie Travis↗

DOE OSTI2025

Global Methane Budget 2000–2020

Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. CH4 is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2), and both emissions and atmospheric concentrations of CH4 have continued to increase since 2007 after a temporary pause. The relative importance of CH4 emissions compared to those of CO2 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in quantifying the factors responsible for the observed atmospheric growth rate arise from diverse, geographically overlapping CH4 sources and from the uncertain magnitude and temporal change in the destruction of CH4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise, and update the global CH4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH4 budget, integrating results of top-down CH4 emission estimates (based on in situ and Greenhouse Gases Observing SATellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full data sets are available), for the previous decade of 2000–2009 and for the year 2020. The revision of the bottom-up budget in this 2025 edition benefits from important progress in estimating inland freshwater emissions, with better counting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double counting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double counting that may exist (average of 23 Tg CH4 yr−1). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH4 yr−1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches. For the 2010–2019 decade, global CH4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH4 yr−1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH4 yr−1 or ∼ 65 % is attributed to direct anthropogenic sources in the fossil, agriculture, and waste and anthropogenic biomass burning (range 350–391 Tg CH4 yr−1 or 63 %–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH4 yr−1 (range 9–40). The 2020 emission rate is the highest of the period and reaches 608 Tg CH4 yr−1 (range 581–627), which is 12 % higher than the average emissions in the 2000s. Since 2012, global direct anthropogenic CH4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH4 yr−1) larger global emissions (669 Tg CH4 yr−1, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH4 yr−1 in Saunois et al. (2016, 2020) respectively), and for the first time uncertainties in bottom-up and top-down budgets overlap. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters. The tropospheric loss of methane, as the main contributor to methane lifetime, has been estimated at 563 [510–663] Tg CH4 yr−1 based on chemistry–climate models. These values are slightly larger than for 2000–2009 due to the impact of the rise in atmospheric methane and remaining large uncertainty (∼ 25 %). The total sink of CH4 is estimated at 633 [507–796] Tg CH4 yr−1 by the bottom-up approaches and at 554 [550–567] Tg CH4 yr−1 by top-down approaches. However, most of the top-down models use the same OH distribution, which introduces less uncertainty to the global budget than is likely justified. For 2010–2019, agriculture and waste contributed an estimated 228 [213–242] Tg CH4 yr−1 in the top-down budget and 211 [195–231] Tg CH4 yr−1 in the bottom-up budget. Fossil fuel emissions contributed 115 [100–124] Tg CH4 yr−1 in the top-down budget and 120 [117–125] Tg CH4 yr−1 in the bottom-up budget. Biomass and biofuel burning contributed 27 [26–27] Tg CH4 yr−1 in the top-down budget and 28 [21–39] Tg CH4 yr−1 in the bottom-up budget. We identify five major priorities for improving the CH4 budget: (i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH4 based on a robust classification of different types of emitting ecosystems; (ii) further development of process-based models for inland-water emissions; (iii) intensification of CH4 observations at local (e.g. FLUXNET-CH4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture, and landfills) to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GKQ9-2RHT (Martinez et al., 2024).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Global patterns and controls of soil organic carbon dynamics as simulated by multiple terrestrial biosphere models. Current status and future directions

Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and loss from soil accounts for a large pro portion of land-atmosphere C exchange. Due to large pool size and variable residence time from years to millennia, even small changes in soil organic C(SOC) have substantial effects on the terrestrial C budget, thereby affecting atmospheric carbon dioxide (CO2)concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain and identifying major driving forces controlling soil C storage and fluxes remains a key research challenge his study has compiled century-long (1901-2010)estimates of SOC storage and heterotrophic respiration (Rh) from ten terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) and two observation based datasets. The ten-TBM ensemble shows that global SOC estimate range from 4 to 2111 Pg C (1 Pg = 10 15 g) with a median value of 1158 Pg C33 in 2010. Modeling approach estimates a broad range of Rh from 35 to 69 Pg C yr -1 with a median value of 51Pg C yr -1 during 200–2010. The largest uncertainty in SOC stocks exists in the 40–65°N latitude band while Rh differences are the largest in the tropics. All the models agreed that climate and land use changes have decreased SOC stocks while elevated CO 2 and atmospheric nitrogen deposition have increased SOC stocks though the response varied significantly among models. Model representations of temperature and moisture sensitivity,nutrient limitation and land use partially explain the divergent estimates of global SOC stocks and soil fluxes in this study. In addition, major sources of uncertainty from model estimation include exclusion of SOC storage in wetlands and peatlands as well as C storage in deep soil layers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

A machine learning pipeline for identifying infiltration managed aquifer recharge locations from satellite imagery in the San Joaquin Valley, California

This study focuses on an agricultural region in California’s Central Valley, USA, where Managed Aquifer Recharge (MAR) is widely implemented to mitigate groundwater depletion under increasing water demand and climate variability. A deep learning and machine learning framework was developed to identify infiltration-MAR locations using satellite imagery and environmental data. The framework integrates surface water detection from Sentinel-2 imagery, geospatial delineation of water bodies, spatiotemporal tracking of water body dynamics, and supervised classification using meteorological, environmental, and topographic variables. The framework was applied to a 2379 km² study area southwest of Fresno, where 765 water bodies were detected, including 139 identified MAR sites based on publicly available datasets and expert knowledge. The classification model achieved an accuracy of 0.94 and an F1 score of 0.85. Feature importance analysis indicates that cropland, normalized difference vegetation index (NDVI), and evaporation are among the most influential predictors for infiltration-MAR. Notably, the framework suggests that engineered water management in infiltration-MAR systems can disrupt or even reverse the expected positive correlation between surface water extent and precipitation. These findings provide physically interpretable insights into the characteristics of existing infiltration-MAR facilities and demonstrate the potential of the proposed framework as a reproducible, interpretable, and potentially transferable tool for data-driven infiltration-MAR identification and inventory development under growing climatic and hydrological uncertainty.

Classification↗

NASA NTRS2011

Daily and Hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We distributed monthly GFED3 emissions during 2003-2009 on a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) active fire observations. We found that patterns of daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of bunting in savannas. On diurnal timescales, our analysis of the GOES active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗

DOE OSTI2021

Evidence for Lignocellulose-Decomposing Enzymes in the Genome and Transcriptome of the Aquatic Hyphomycete Clavariopsis aquatica

Fungi are ecologically outstanding decomposers of lignocellulose. Fungal lignocellulose degradation is prominent in saprotrophic Ascomycota and Basidiomycota of the subkingdom Dikarya. Despite ascomycetes dominating the Dikarya inventory of aquatic environments, genome and transcriptome data relating to enzymes involved in lignocellulose decay remain limited to terrestrial representatives of these phyla. We sequenced the genome of an exclusively aquatic ascomycete (the aquatic hyphomycete Clavariopsis aquatica), documented the presence of genes for the modification of lignocellulose and its constituents, and compared differential gene expression between C. aquatica cultivated on lignocellulosic and sugar-rich substrates. We identified potential peroxidases, laccases, and cytochrome P450 monooxygenases, several of which were differentially expressed when experimentally grown on different substrates. Additionally, we found indications for the regulation of pathways for cellulose and hemicellulose degradation. Our results suggest that C. aquatica is able to modify lignin to some extent, detoxify aromatic lignin constituents, or both. Such characteristics would be expected to facilitate the use of carbohydrate components of lignocellulose as carbon and energy sources.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2006

A Test of Sensitivity to Convective Transport in a Global Atmospheric CO2 Simulation

Two approximations to convective transport have been implemented in an offline chemistry transport model (CTM) to explore the impact on calculated atmospheric CO2 distributions. GlobalCO2 in the year 2000 is simulated using theCTM driven by assimilated meteorological fields from the NASA s Goddard Earth Observation System Data Assimilation System, Version 4 (GEOS-4). The model simulates atmospheric CO2 by adopting the same CO2 emission inventory and dynamical modules as described in Kawa et al. (convective transport scheme denoted as Conv1). Conv1 approximates the convective transport by using the bulk convective mass fluxes to redistribute trace gases. The alternate approximation, Conv2, partitions fluxes into updraft and downdraft, as well as into entrainment and detrainment, and has potential to yield a more realistic simulation of vertical redistribution through deep convection. Replacing Conv1 by Conv2 results in an overestimate of CO2 over biospheric sink regions. The largest discrepancies result in a CO2 difference of about 7.8 ppm in the July NH boreal forest, which is about 30% of the CO2 seasonality for that area. These differences are compared to those produced by emission scenario variations constrained by the framework of Intergovernmental Panel on Climate Change (IPCC) to account for possible land use change and residual terrestrial CO2 sink. It is shown that the overestimated CO2 driven by Conv2 can be offset by introducing these supplemental emissions.

Bian, H.↗

NASA NTRS2011

Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003.2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS) ]derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top ]down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗

DOE OSTI2018

A Modular and Flexible High-Frequency-Link Transformer with a Reduced Device Count and Zero High-Side Devices

In general, large power transformers (LPTs) are not interchangeable with each other and their high costs prohibit extensive spare inventories more so considering that on an average only 1.3 LPTs are manufactured for individual design. The latter pose a further challenge since given that the several existing LPTs are reaching their end of service lives, loss of plurality of such LPTs, that form the backbone of U.S. power grid, will clearly run into the problem of energy security related to the non-availability of sufficient spares (and extended lead time) exacerbated further by the fact that these spares are not interchangeable for installations at different locations. Conventional LPT cost millions of dollars and weighs significantly between approximately 100 and 400 tons. Two raw materials—copper and electrical steel—account for over 50 percent of the total cost of an LPT. In recent years, the price volatility of these two commodities in the global market has affected the manufacturing conditions and procurement strategy for LPTs. Transportation is also an important element of the total LPT cost, because an LPT can weigh significantly and often requires long-distance transport. Transporting an LPT is challenging—its large dimensions and heavy weight pose unique requirements to ensure safe and efficient transportation. Current road, rail, and port conditions are such that transportation is taking more time and becoming more expensive. Conventional low-frequency LPTs typically follow a monolithic approach to design due to historical reasons that need to transition to more modular and flexible (e.g., in voltage, impedance, and power flow) designs with ability to seamlessly/near-seamlessly scale. They should also have the ability to incorporate new technologies without in all cases redoing a LPT design from scratch. Given that the cost of raw materials has continued to increase, next-generation LPTs need to pursue avenues for reducing these costs. An added necessity is to reduce the transportability cost, which is significant in conventional LPTs. Further, given that LPTs are for the long term, they need to be durable, efficient, and fault tolerant with overloading capability. Given this backdrop, the objective and accomplishment of this one-year DOE (SPONSOR) R&D project, led by small business NextWatt LLC (PRIME, Lead PI: Dr. Sudip K. Mazumder) and University of Arkansas at Fayetteville (SUBAWARDEE, PI: Dr. Juan Balda) were to explore the design of a (8 – 20 kHz) high-frequency-link (HFL) based 100-MVA LPT with nominal voltage of 115/69 kV, with $15 - $22 dollars US per kVA when manufactured in “moderate” volume, with 99% energy-conversion efficiency, with 300% reduction in both volume and weight compared to a conventional LPT with the same electrical ratings, with impedance variation greater than 5%, with direct AC/AC power conversion capability, with very-high energy-conversion efficiency (using wide-bandgap SiC based field effect MOSFET devices) over a wide operating temperature, with reduction in both volume and weight with regard to conventional low frequency LPT, and with significant reduction in number of devices compared to state of the art solid state transformer topology.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2020

Evaluating China's fossil-fuel CO2 emissions from a comprehensive dataset of nine inventories

China's fossil-fuel CO2 (FFCO2) emissions accounted for approximately 28 % of the global total FFCO2 in 2016. An accurate estimate of China's FFCO2 emissions is a prerequisite for global and regional carbon budget analyses and the monitoring of carbon emission reduction efforts. However, significant uncertainties and discrepancies exist in estimations of China's FFCO2 emissions due to a lack of detailed traceable emission factors (EFs) and multiple statistical data sources. Here, we evaluated China's FFCO2 emissions from nine published global and regional emission datasets. These datasets show that the total emissions increased from 3.4 (3.0–3.7) in 2000 to 9.8 (9.2–10.4) Gt CO2 per yr in 2016. The variations in these estimates were largely due to the different EF (0.491–0.746 t C per t of coal) and activity data. The large-scale patterns of gridded emissions showed a reasonable agreement, with high emissions being concentrated in major city clusters, and the standard deviation mostly ranged from 10 % to 40 % at the provincial level. However, patterns beyond the provincial scale varied significantly, with the top 5 % of the grid level accounting for 50 %–90 % of total emissions in these datasets. Our findings highlight the significance of using locally measured EF for Chinese coal. To reduce uncertainty, we recommend using physical CO2 measurements and use these values for dataset validation, key input data sharing (e.g., point sources), and finer-resolution validations at various levels.

Pengfei Han↗

NASA NTRS2012

Nucleobases and Prebiotic Molecules in Organic Residues Produced from the Ultraviolet Photo-Irradiation of Pyrimidine in NH3 and H2O+NH3 Ices

Although not yet identified in the interstellar medium (ISM), N-heterocycles including nucleobases the information subunits of DNA and RNA are present in carbonaceous chondrites, which indicates that molecules of biological interest can be formed in non-terrestrial environments via abiotic pathways. Recent laboratory experiments and ab-initio calculations have already shown that the irradiation of pyrimidine in pure H2O ices leads to the formation of a suite of oxidized pyrimidine derivatives, including the nucleobase uracil. In the present work, NH3:pyrimidine and H2O:NH3:pyrimidine ice mixtures with different relative proportions were irradiated with UV photons under astrophysically relevant conditions. Liquid- and gas-chromatography analysis of the resulting organic residues has led to the detection of the nucleobases uracil and cytosine, as well as other species of prebiotic interest such as urea and small amino acids. The presence of these molecules in organic residues formed under abiotic conditions supports scenarios in which extraterrestrial organics that formed in space and were subsequently delivered to telluric planets via comets and meteorites could have contributed to the inventory of molecules that triggered the first biological reactions on their surfaces.

Nuevo, Michel↗

NASA NTRS2021

Bias-Correcting Carbon Fluxes Derived From Land-Surface Satellite Data for Retrospective and Near Real-Time Assimilation Systems

The ability to monitor and understand natural and anthropogenic variability in atmospheric carbon dioxide(CO2) is a growing need of many stakeholders across the world. Systems that assimilate satellite observations, given their short latency and dense spatial coverage, into high resolution global models are valuable, if not essential, tools for addressing this need. A notable drawback of modern assimilation systems is the long latency of many vital in-put datasets, e.g., inventories, in situ measurements, and re-processed remote-sensing data can trail the current date by months to years. This paper describes techniques for bias-correcting surface fluxes derived from satellite observations of the Earth’s surface to be consistent with constraints from inventories and in situ CO2 datasets. The techniques are applicable in both short-term forecasts and retrospective simulations, thus taking advantage of the coverage and short latency of satellite data while reproducing the major features of long-term inventory and in situ records. Our approach begins with a standard collection of diagnostic fluxes which incorporate a variety of remote-sensing driver data, viz. vegetation indices, fire radiative power, and nighttime lights. We then apply an empirical sink so that global budgets of the diagnostic fluxes match given atmospheric and oceanic growth rates for each year. This step removes coherent, systematic flux errors that produce biases inCO2which mask the signals an assimilation system hopes to capture. Depending on the simulation mode, the empirical sink uses different choices of atmospheric growth rates: estimates based on observations in retrospective mode and projections based on seasonal fore-casts of sea surface temperature in forecasting mode. The retrospective fluxes, when used in simulations with NASA’s Goddard Earth Observing System (GEOS), reproduce marine boundary layer measurements with comparable skill to those using fluxes from a modern inversion system. The forecasted fluxes show promising accuracy in their application to the analysis of changes in the carbon cycle as they occur.

CO2↗

DOE OSTI2017

An integrated environmental and health performance quantification model for pre-occupancy phase of buildings in China

To comprehensively pre-evaluate the damages to both the environment and human health due to construction activities in China, this paper presents an integrated building environmental and health performance (EHP) assessment model based on the Building Environmental Performance Analysis System (BEPAS) and the Building Health Impact Analysis System (BHIAS) models and offers a new inventory data estimation method. The new model follows the life cycle assessment (LCA) framework and the inventory analysis step involves bill of quantity (BOQ) data collection, consumption data formation, and environmental profile transformation. The consumption data are derived from engineering drawings and quotas to conduct the assessment before construction for pre-evaluation. The new model classifies building impacts into three safeguard areas: ecosystems, natural resources and human health. Thus, this model considers environmental impacts as well as damage to human wellbeing. The monetization approach, distance-to-target method and panel method are considered as optional weighting approaches. Finally, nine residential buildings of different structural types are taken as case studies to test the operability of the integrated model through application. The results indicate that the new model can effectively pre-evaluate building EHP and the structure type significantly affects the performance of residential buildings.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

PV O&M Cost Model [SWR-21-14]

This tool presents a method for calculating costs associated with the operation and maintenance (O&M) of photovoltaic (PV) systems. The tool compiles details regarding the cost and frequency of multiple O&M services to estimate annual O&M costs ($/year) for each year of an analysis period, the net present value ($) of life cycle costs accumulated over the analysis period, and the reserve account amount ($) that might be required to fund unexpected repairs. The reserve account includes parts inventory and is important for providing a source of funds to make repairs quickly and avoid lost production. This method allows a detailed selection of services to perform based on system size, market served (e.g., residential, commercial, or utility), type and configuration of system components (e.g., micro-, string, or central inverter), and site and environmental conditions (e.g., pollen, bird populations) which is an improvement over simple per unit valuations of O&M costs ($/kW/year). This model also distinguishes costs that vary from year to year and increase at different rates over time as modeled by heuristic failure distributions (e.g., Weibull or Lognormal distribution) based on actuarial data for many of the services.

Walker, Andy↗

NASA NTRS1974

Evaluation of ERTS-1 data applications to geologic mapping, structural analysis and mineral resource inventory of South America with special emphasis on the Andes Mountain region

The author has identified the following significant results. A color composite of image E1010-14035, dated 2 August 1972, covers the west central Bolivian Altiplano near Salar de Coipasa. It clearly shows the distribution of surface water and scant patches of vegetation. The Salar de Coipasa is the largest body of water in the area, about 130 sq km of dark blue fresh water. A lighter blue area south of the lake suggests a thin cover of highly saline water superposed on salt beds. The scattered vegetation patches are presumed to be native grasses, lichens, and possibly Indian potato and maiz areas. A detailed study has been made of the scene which provides 12 different interpretive overlays including geology, volcanology, soils, hydrology, and relative permeability. It was found that color composites provide at least 40% more information that do black and white renditions. An excellent example of change detection was provided by image E1244-14051, dated 24 March 1973. Water in the Salar de Coipasa had more than doubled as a result of the rains of the Bolivian winter, which generally occur in the February-March period. The Salars are excellent and highly sensitive moisture indicators in this highly arid region.

Carter, W. D.↗

NASA NTRS2001

Learning Styles of Pilots Currently Qualified in United States Air Force Aircraft

Kolb's Learning Style Inventory was used to identify the predominant learning styles of pilots currently qualified in United States Air Force aircraft. The results indicate that these pilots show a significant preference for facts and things over people and feelings. By understanding the preferred learning styles of the target population, course material can be developed that take advantage of the strengths of these learning styles. This information can be especially useful in the future design of cockpit resource management training. The training program can be developed to demonstrate both that there are different learning styles and that it is possible to take advantage of the relative strengths of each of these learning styles.

Kanske, Craig A.↗

NASA NTRS2021

Classifying Forest Type in the National Forest Inventory Context with Airborne Hyperspectral and Lidar Data

Forest structure and composition regulate a range of ecosystem services, including biodiversity, water and nutrient cycling, and wood volume for resource extraction. Forest type is an important metric measured in the US Forest Service Forest Inventory and Analysis (FIA) program, the national forest inventory of the USA. Forest type information can be used to quantify carbon and other forest resources within specific domains to support ecological analysis and forest management decisions, such as managing for disease and pests. In this study, we developed a methodology that uses a combination of airborne hyperspectral and lidar data to map FIA-defined forest type between sparsely sampled FIA plot data collected in interior Alaska. To determine the best classification algorithm and remote sensing data for this task, five classification algorithms were tested with six different combinations of raw hyperspectral data, hyperspectral vegetation indices, and lidar-derived canopy and topography metrics. Models were trained using forest type information from 632 FIA subplots collected in interior Alaska. Of the thirty model and input combinations tested, the random forest classification algorithm with hyperspectral vegetation indices and lidar-derived topography and canopy height metrics had the highest accuracy (78% overall accuracy). This study supports random forest as a powerful classifier for natural resource data. It also demonstrates the benefits from combining both structural (lidar) and spectral (imagery) data for forest type classification.

random forest↗

DOE OSTI2019

Radiation Leakage and the Precision of Characterizing Nuclear Material Using Calorimetric Assay - 19233

For measuring a waste drum containing multi-nuclide radioactive material calorimetric assay is often combined with gamma ray and neutron measurements. To reduce the methodological uncertainties of the inventory determination in a multi-nuclide matrix, the escaping radiation must be quantized as much as the encapsulated gamma-rays and α-, β-, n- particles depositing radiological heat inside the drum. To differentiate the possible variety of heat sources in a radioactive waste drum, Monte Carlo simulations are utilized resembling the waste drum and the calorimeter in both, their geometries as well as the material compositions. MCNP6-based numerical imaging of the Large Volume Calorimeter (LVC) designed by KEP Nuclear(France) allows simulating various scenarios for different particles types, energies and source locations to accompany and support the interpretation of calorimetric KEP-LVC measurements anticipated within the CHANCE project. For the analyses, the particle flux and energy deposition in each layer of the calorimeter are displayed. The results yield that a significant part of the emitted radiation leaves the system and does not contribute to the heat deposited inside the drum. As an example, the particle flux study of a 200 L mock-up drum placed inside the KEP-LVC calorimeter is discussed. A tally 4 with mesh option for both gamma and neutrons up to 5 MeV simulates the mean flux in each cell and for various source location and source distribution patterns. The expected energy deposition is cumulated for each layer, and over the whole energy range it reveals that actually a small but well known fraction of particles escapes the LVC calorimeter. This makes it a very suitable apparatus for the anticipated experiments on large and heterogeneous waste drums. The results suggest that the most interesting cases would be polyethylene, bitumen and concrete matrices [3, 5]. However, it must be kept in mind that the high-energy part of the gamma and neutron radiation flux can reach the reference chamber of the calorimeter and deposit some energy there, which may compromise the calibration and cause double-bias. The simulations showed that, depending on source location and power, neutron and high-energy gamma radiation leakage can influence the heat measurements differently. In general, part of the simulation results suggest that for waste drums with a high emission rate the accuracy of calorimetric assay can be decreased due to radiation escape. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗