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

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Parametric analysis of synthetic aperture radar data for the study of forest stand characteristics

A parametric analysis of a Gulf Coast forest stand was performed using multipolarization, multipath airborne SAR data, and forest plot properties. Allometric equations were used to compute the biomass and basal area for the test plots. A multiple regression analysis with stepwise selection of independent variables was performed. It is found that forest stand characteristics such as biomass, basal area, and average tree height are correlated with SAR data.

Wu, Shih-Tseng↗
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.↗
NASA NTRS1999

Interannual Variabilities in Tropical Tropospheric Ozone

This paper presents the first detailed characterization of interannual variability in tropical tropospheric column ozone (TCO) to delineate the relative importance of biomass burning and large-scale transport. TCO time series are derived from 20 years (1979-1998) of total ozone mapping spectrometer (TOMS) data using the convective cloud differential (CCD) method. Our study identifies three regions in the tropics with distinctly different characteristics related to interannual variability. These three regions are the eastern Pacific, Atlantic, and western Pacific. The Atlantic region indicates a quasi-biennial oscillation (QBO) in TCO which is out of phase with the QBO in stratospheric ozone. This is consistent with the photochemical control of this region by ozone-producing precursors. The observed pattern however does not seem to be related to interannual variability in ozone precursors related to biomass burning. Instead it appears to be a manifestation of the UV modulation of upper tropospheric chemistry on a QBO time scale caused by stratospheric ozone. During El Nino events there is anomalously low TCO in the eastern Pacific and high values in the western Pacific, indicating the effects of convectively-driven transport. The observed increase of 10-20 DU in TCO in the Indonesian region in the western Pacific during the recent 1997-1998 El Nino was associated with large-scale fires which may have contributed 5-10 DU of the total increase.

Ziemke, Jerry R.↗
NASA NTRS1998

Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neural Networks

A number of satellite sensor systems will collect large data sets of the Earth's surface during NASA's Earth Observing System (EOS) era. Efforts are being made to develop efficient algorithms that can incorporate a wide variety of spectral data and ancillary data in order to extract vegetation variables required for global and regional studies of ecosystem processes, biosphere-atmosphere interactions, and carbon dynamics. These variables are, for the most part, continuous (e.g. biomass, leaf area index, fraction of vegetation cover, vegetation height, vegetation age, spectral albedo, absorbed photosynthetic active radiation, photosynthetic efficiency, etc.) and estimates may be made using remotely sensed data (e.g. nadir and directional optical wavelengths, multifrequency radar backscatter) and any other readily available ancillary data (e.g., topography, sun angle, ground data, etc.). Using these types of data, neural networks can: 1) provide accurate initial models for extracting vegetation variables when an adequate amount of data is available; 2) provide a performance standard for evaluating existing physically-based models; 3) invert multivariate, physically based models; 4) in a variable selection process, identify those independent variables which best infer the vegetation variable(s) of interest; and 5) incorporate new data sources that would be difficult or impossible to use with conventional techniques. In addition, neural networks employ a more powerful and adaptive nonlinear equation form as compared to traditional linear, index transformations, and simple nonlinear analyses. These neural networks attributes are discussed in the context of the authors' investigations of extracting vegetation variables of ecological interest.

Kimes, Daniel S.↗
NASA NTRS2020

Forest Potential Productivity Mapping by Linking Remote-Sensing-Derived Metrics to Site Variables

A fine-resolution region-wide map of forest site productivity is an essential need for effective large-scale forestry planning and management. In this study, we incorporated Sentinel-2 satellite data into an increment-based measure of forest productivity (biomass growth index (BGI)) derived from climate, lithology, soils, and topographic metrics to map improved BGI (iBGI) in parts of North American Acadian regions. Initially, several Sentinel-2 variables including nine single spectral bands and 12 spectral vegetation indices (SVIs) were used in combination with forest management variables to predict tree volume/ha and height using Random Forest. The results showed a 10–12 % increase in out of bag (OOB) r2when Sentinel-2 variables were included in the prediction of both volume and height together with BGI. Later, selected Sentinel-2 variables were used for biomass growth prediction in Maine, USA and New Brunswick, Canada using data from 7738 provincial permanent sample plots. The Sentinel-2 red-edge position (S2REP) index was identified as the most important variable over others to have known influence on site productivity. While a slight improvement in the iBGI accuracy occurred compared to the base BGI model (~2%), substantial changes to coefficients of other variables were evident and some site variables became less important when S2REP was included.

site productivity↗
NASA NTRS1988

Continental scale variability in vegetation reflectance and its relationship to canopy morphology

The spectral canopy reflectance, biomass, and projected leaf-area index (LAI) of widely dispersed plots of a North American coastal plant were measured in order to study potential impacts of continental-scale environmental variability on the assumptions underlying remote vegetation analysis. Systematic changes in the canopy geometry and resultant near-infrared reflectance of this plant were noted. Mean infrared canopy reflectances of canopies in the northern half of the range were shown to nearly double those of the southern half. It is suggested that the difference results from divergent canopy morphologies, with the northern canopies presenting greater horizontally projected LAIs per unit biomass than southern canopies.

Bartlett, D. S.↗
DOE OSTI2024

The Role of Biofuels and Biomass Feedstocks for Decarbonizing the U.S. Economy by 2050 - (DECARB) Decarbonizing Energy Through Collaborative Analysis of Routes and Benefits

Utilizing biomass resources, such as cellulosic biomass and waste, can greatly contribute to decarbonization efforts in the U.S. economy. The U.S. bioenergy sector includes corn ethanol production, biodiesel, renewable diesel production, and the utilization of biomass wastes for electricity generation being the primary applications. Within the electricity sector, biopower can play a crucial role as a stable low-carbon resource. Enhancing the electricity mix's diversity could enhance grid reliability. If the issues regarding hot gas cleanup can be resolved, flexible biopower resources like biomass gasification facilities could complement the integration of variable renewable energy sources due to their quick ramp-up and ramp-down times. The criticality of bioenergy deployment lies in its ability to decarbonize hard-to-electrify sectors, such as aviation, where alternative decarbonization options may not be viable in the short term. Moreover, bioenergy has the potential to be converted into process heating, building materials, and plastics, which are not considered in this study. A set of pathways was carefully chosen to represent viable options for converting ample herbaceous and woody cellulosic feedstocks into fuels, chemicals, and electricity in this study. In conclusion, biomass pathways provide flexibility by generating various types of bioenergy and bioproducts, including electricity, hydrogen, liquid fuels, biochemicals, and bioplastics. When paired with carbon dioxide capture and storage (CCS), specific bioenergy approaches can effectively extract carbon dioxide from the atmosphere, thus providing an effective decarbonization option for the transportation sector.

09 BIOMASS FUELS↗
NASA NTRS2020

Mapping tall shrub biomass in Alaska at landscape scale using structure-from-motion photogrammetry and lidar

Warming in arctic and boreal regions is increasing shrub cover and biomass. In southcentral Alaska, willow (Salix spp.) and alder (Alnus spp.) shrubs grow taller than many tree species and account for a substantial proportion of aboveground biomass, yet they are not individually measured as part of the operational Forest Inventory and Analysis (FIA) Program. The goal of this research was to test methods for landscape-scale mapping of tall shrub biomass in upper montane and subalpine environments using FIA-type plot measurements (n = 51) and predictor variables from imagery-based structure-from-motion (SfM) and airborne lidar. Specifically, we compared biomass models constructed from imagery acquired by unmanned aerial vehicle (UAV; ~1.7 cm pixels), imagery from the NASA Goddard's Lidar, Hyperspectral, and Thermal Airborne Imager (G-LiHT; ~3.1 cm pixels), and concomitant G-LiHT small-footprint lidar. Tall shrub biomass was most accurately predicted at 5 m resolution (R^2 = 0.81, RMSE = 1.09 kg/sq. m) using G-LiHT SfM color and structure variables. Lidar-only models had lower precision (R^2 = 0.74, RMSE = 1.26 kg/sq. m), possibly due to reduced model information content from variable multicollinearity or lower data density. Separate models for upper montane zones with trees and shrubs and subalpine zones with only shrubs were always chosen over single models based on minimization of Akaike's Information Criterion, indicating the need for variable sets robust to overhanging tree canopy. Decreasing point density from UAV (5000–8000 pts./sq. m) to the G-LiHT SfM point cloud (500–2000 pts./sq. m) had little impact on model fit, suggesting that high-resolution airborne imagery can extend SfM approaches well beyond line-of-sight restrictions for UAV platforms. Overall, our results confirmed that SfM from high-resolution imagery is a viable approach to estimate shrub biomass in the boreal region, especially when an existing lidar terrain model and local field calibration data are available to quantify uncertainty in the SfM point cloud and landscape-scale estimates of shrub biomass.

Michael Alonzo↗
DOE OSTI2024

Corn stover variability drives differences in bisabolene production by engineered Rhodotorula toruloides

Microbial conversion of lignocellulosic biomass represents an alternative route for production of biofuels and bioproducts. While researchers have mostly focused on engineering strains such as Rhodotorula toruloides for better bisabolene production as a sustainable aviation fuel, less is known about the impact of the feedstock heterogeneity on bisabolene production. Critical material attributes like feedstock composition, nutritional content, and inhibitory compounds can all influence bioconversion. Further, the given feedstocks can have a marked influence on selection of suitable pretreatment and hydrolysis technologies, optimizing the fermentation conditions, and possibly even modifying the microorganism's metabolic pathways, to better utilize the available feedstock. Here, this work aimed to examine and understand how variations in corn stover batches, anatomical fractions, and storage conditions impact the efficiency of bisabolene production by R. toruloides. All of these represent different facets of feedstock heterogeneity. Deacetylation, mechanical refining, and enzymatic hydrolysis of these variable feedstocks served as the basis of this research. The resulting hydrolysates were converted to bisabolene via fermentation, a sustainable aviation fuel precursor, using an engineered R. toruloides strain. This study showed that different sources of feedstock heterogeneity can influence microbial growth and product titer in counterintuitive ways, as revealed through global analysis of protein expression. The maximum bisabolene produced by R. toruloides was on the stalk fraction of corn stover hydrolysate (8.89 ± 0.47 g/L). Further, proteomics analysis comparing the protein expression between the anatomic fractions showed that proteins relating to carbohydrate metabolism, energy production, and conversion as well as inorganic ion transport metabolism were either significantly upregulated or downregulated. Specifically, downregulation of proteins related to the iron–sulfur cluster in stalk fraction suggests a coordinated response by R. toruloides to maintain overall metabolic balance, and this was corroborated by the concentration of iron in the feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2022

MSW Variability Mapping and Conversion to Biofuel

MSW (Municipal Solid Waste) is a form of biomass which consists of categorized components of waste/trash. The general categories are paper, yard trash, construction & debris, appliances, tires, glass, metals, aluminum & steel cans, plastics, organics, inorganics, and HHW (Household Hazardous Waste). This project focuses on the factors within a region or population that contribute to variability in the composition of MSW and in turn MSW’s convertibility to biofuel. A list of contributors was determined (Social Vulnerability Index, Access to Public Transportation, Racial Distribution, GDP, Personal Income) and then JMP was used to perform a Multivariate analysis to determine correlations and a Partial Least-Squares regression to determine Variable Importance Plots for each MSW category. In addition to data analysis, the convertibility of MSW to biofuel was studied via microwave pyrolysis system in order to separate and characterize the various gaseous and bio-oil products.

09 BIOMASS FUELS↗
NASA NTRS1987

Forest biomass, canopy structure, and species composition relationships with multipolarization L-band synthetic aperture radar data

The effect of forest biomass, canopy structure, and species composition on L-band synthetic aperature radar data at 44 southern Mississippi bottomland hardwood and pine-hardwood forest sites was investigated. Cross-polarization mean digital values for pine forests were significantly correlated with green weight biomass and stand structure. Multiple linear regression with five forest structure variables provided a better integrated measure of canopy roughness and produced highly significant correlation coefficients for hardwood forests using HV/VV ratio only. Differences in biomass levels and canopy structure, including branching patterns and vertical canopy stratification, were important sources of volume scatter affecting multipolarization radar data. Standardized correction techniques and calibration of aircraft data, in addition to development of canopy models, are recommended for future investigations of forest biomass and structure using synthetic aperture radar.

Sader, Steven A.↗
NASA NTRS1988

Estimating forest biomass and volume using airborne laser data

An airborne pulsed laser system was used to obtain canopy height data over a southern pine forest in Georgia in order to predict ground-measured forest biomass and timber volume. Although biomass and volume estimates obtained from the laser data were variable when compared with the corresponding ground measurements site by site, the present models are found to predict mean total tree volume within 2.6 percent of the ground value, and mean biomass within 2.0 percent. The results indicate that species stratification did not consistently improve regression relationships for four southern pine species.

Nelson, Ross↗
NASA NTRS1977

Use of near infrared/red radiance ratios for estimating vegetation biomass and physiological status

The application of photographic infrared/red (ir/red) reflectance or radiance ratios for the estimation of vegetation biomass and physiological status were investigated by analyzing in situ spectral reflectance data from experimental grass plots. Canopy biological samples were taken for total wet biomass, total dry biomass, leaf water content, dry green biomass, dry brown biomass, and total chlorophyll content at each sampling date. Integrated red and photographic infrared radiances were regressed against the various canopy or plot variables to determine the relative significance between the red, photographic infrared, and the ir/red ratio and the canopy variables. The ir/red ratio is sensitive to the photosynthetically active or green biomass, the rate of primary production, and actually measures the interaction between the green biomass and the rate of primary production within a given species type. The ir/red ratio resulted in improved regression significance over the red or the ir/radiances taken separately. Only slight differences were found between ir/red ratio, the ir-red difference, the vegetation index, and the transformed vegetation index. The asymptotic spectral radiance properties of the ir, red, ir/red ratio, and the various transformations were evaluated.

Tucker, C. J.↗
NASA NTRS2001

Tropospheric Ozone and Biomass Burning

This paper studies the significance of pyrogenic (e.g., biomass burning) emissions in the production of tropospheric ozone in the tropics associated with the forest and savanna fires in the African, South American, and Indonesian regions. Using aerosol index (Al) and tropospheric column ozone (TCO) time series from 1979 to 2000 derived from the Nimbus-7 and Earth Probe TOMS measurements, our study shows significant differences in the seasonal and spatial characteristics of pyrogenic emissions north and south of the equator in the African region and Brazil in South America. In general, they are not related to the seasonal and spatial characteristics of tropospheric ozone in these regions. In the Indonesian region, the most significant increase in TCO occurred during September and October 1997, following large-scale forest and savanna fires associated with the El Nino-induced dry season. However, the increase in TCO extended over most of the western Pacific well outside the burning region and was accompanied by a decrease in the eastern Pacific resembling a west-to-east dipole about the date-line. The net increase in TCO integrated over the tropical region between 15 deg N and 15 deg S was about 6-8 Tg (1 Tg = 10(exp 12) gm) over the mean climatological value of about 72 Tg. This increase is well within the range of interannual variability of TCO in the tropical region and does not necessarily suggest a photochemical source related to biomass burning. The interannual variability in TCO appears to be out of phase with the interannual variability of stratospheric column ozone (SCO). These variabilities seem to be manifestations of solar cycle and quasibiennial oscillations.

Chandra, Sushil↗
DOE OSTI2025

Data from a throughfall exclusion experiment: Fine root dynamics, morphology, chemistry, and AMF colonization across four lowland Panamanian forests

Fine roots regulate forest nutrient, carbon, and water cycling, yet their variation within and among tropical forests remains under-characterized. We quantified root productivity, disappearance, and stocks to 1 m using minirhizotron imaging, and we measured morphology, elemental composition [root carbon (C), root nitrogen (N), root phosphorus (P)], and arbuscular mycorrhizal fungi (AMF) colonization to 20 cm using ingrowth cores and sequential coring. Sampling took place in four distinct lowland Panamanian forests (32 plots; 8 per forest) from 2018 through 2022 under control and throughfall-exclusion (drought) treatments in the Panama Rainforest Changes with Experimental Drying (PARCHED) experiment.The dataset is presented as an Excel workbook with six tabs. The first tab is the data dictionary. Tab S1 contains ingrowth-core production and mortality, morphology and soil moisture. Tab S2 contains sequential-coring standing stocks with associated morphology and soil moisture. Tab S3 contains minirhizotron row data records to 1 m depth, including per-frame root length and diameter, normalized length metrics, and session timing. Tab S4 contains AMF colonization. Tab S5 contains fine-root chemistry at 0–10 cm, reporting %P, %C, %N, and C:N for samples collected via ingrowth cores and sequential-coring standing stocks. CSV mirrors for each tab are provided, and a KML file supplies coordinates for all 32 plots.Key variables span live and dead fine-root biomass (and coarse fractions where applicable), specific root length (SRL) and area (SRA), diameter, root tissue density (RTD), soil moisture, AMF colonization, root %N, %C, %P, and C:N, along with minirhizotron root length and diameter. Depth, season, treatment, and plot/site identifiers are included to support cross-tab integration and analysis from 0–100 cm (minirhizotron) and 0–20 cm (cores).Units are reported in-column and missing values are coded as NA. No special software is required to open or use the files (Excel, CSV, and KML compatible).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Bacterial biomass and heterotrophic potential in the waters of the Chesapeake Bay plume and contiguous continental shelf

Seasonal baseline data on bacterial biomass and heterotrophic uptake in the Chesapeake Bay plume and contiguous Atlantic Ocean shelf waters are discussed. Viable count bacterial numbers in surface water samples collected during June 1980 ranged from a maximum of 190,000 MPN (most probable number)/ml at the Bay mouth to a minimum of 7900 MPN/ml offshore. Similarly, direct count densities ranged from 1,800,000 BU (bacterial units)/ml to 24,000 BU/ml. Heterotrophic potential (V max) was largest at the Bay mouth and lowest offshore. Biomass and V max values usually decreased with depth although subsurface maxima were occasionally observed at inshore stations. Correlation of biomass and heterotrophic potential data with selected hydrographic variables was determind with a nonparametric statistic. Results indicate viable counts are positively and significantly correlated with total chlorophyll, temperature, direct count and V max during June 1980; significant negative correlations are obtained with salinity and depth. Calculations of bacterial standing crop are discussed.

Kator, H. I.↗