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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Considering coasts: Adapting terrestrial models to characterize coastal wetland ecosystems

The Energy Exascale Earth System Model (E3SM) simulates fully coupled processes and interactions among water, energy, carbon and nutrient cycles. E3SM connects vegetation and soil dynamics through nutrient uptake, plant production, litterfall and decomposition as a function of abiotic parameters (e.g. temperature and moisture). However, E3SM is designed to characterize terrestrial ecosystems and connects land and open ocean systems using a single streamflow transport term, ignoring the complex dynamics of energy, water, carbon, and nutrients in coastal systems. The goals of our project were to: (1) Parameterize a point version of E3SM to capture coastal wetland habitats and (2) Determine marsh community responses to increased temperature and elevated CO 2 . We adapted a version of the E3SM land model, previously configured to represent forested bog hydrology to a coastal ecosystem using datasets from field experiments conducted at the Smithsonian Environmental Research Center's Global Change Research Wetland (GCReW). Tidal forcing in a marsh environment was simulated using a two-column system in which the columns are connected by lateral hydrologic flows. One column simulates interactions between vegetation and soil while a second column simulates variation in water level (both tidal and sea level rise). The updated model captures many aspects of the field experiments, showing that plant community responses to environmental change are non-linear, non-additive and different between plant types. Elevated CO 2 treatments increased C 3 plant biomass more than C 4 (33% vs 17%). Temperature exacerbated CO 2 responses in C 3 plants (0 °C: 26%, 5.1 °C: 56%). We were more successful at characterizing C 3 than C 4 responses and simulating above rather than belowground biomass production. Furthermore, the next steps will include updates to key physiological parameters such as root:shoot carbon allocation and the addition of mechanistic feedbacks between vegetation and biogeochemical processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Implications of Global Change for the Co-Evolution of Argentina's Integrated Energy-Water-Land Systems

This study seeks to understand how Argentina’s energy, water, and land (EWL) systems will co-evolve under a representative array of human and earth system influences, including socioeconomic change, climate change, and climate policy. To capture Argentina’s sub-national EWL dynamics in the context of global change, we couple the Global Change Analysis Model with a suite of consistent, gridded sectoral downscaling models to explore multiple stakeholder-engaged scenarios. Across scenarios, Argentina has the economic opportunity to use its vast land resources to satisfy growing domestic and international demand for crops, such as oil (e.g., soy) and biomass. The human (rather than earth) system produces the most dominant changes in mid-century EWL resource use. A Reference scenario characterized by modest socioeconomic growth projects a 40% increase in Argentina’s agricultural production by 2050 (relative to 2020) by using 50,000 km 2 of additional cropland and 40% more water. A Climate Policy scenario designed to achieve net-zero carbon emissions globally shortly after mid-century projects that Argentina could use 100,000 km 2 of additional land (and 65% more water) to grow biomass and other crops. The burden of navigating these national opportunities and challenges could fall disproportionately on a subset of Argentina’s river basins. The Colorado and Negro basins could experience moderate-to-severe water scarcity as they simultaneously navigate substantial irrigated crop demand growth and climate-induced declines in natural water availability. Argentina serves as a generalizable testbed to demonstrate that multi-scale EWL planning challenges can be identified and managed more effectively via integrated analysis of coupled human-earth systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

The effects of expression of a hyperthermophilic endoglucanase and nutrient conditions on poplar growth and physiology

Abstract Efficient production and processing of poplar biomass feedstock requires costly pretreatments and enzyme additives. Transgenic alterations of poplar can reduce the need for these inputs by increasing biomass, improving lignocellulose quality and enhancing nutrient uptake. Previously, a transgenic line of poplar expressing a bacterial hyperthermophilic endoglucanase (TnCelB) in Populus alba × grandidentata (P39) was developed and characterized. This study reports the effects on the TnCelB transgenic poplar line under a reduced nutrient treatment. Overall, the nutrient treatment was the source of more observed significant differences than the genotype. Wild type and TnCelB poplar had similar responses in biomass allocation and net photosynthesis. TnCelB trees had a wrinkled leaf phenotype and relative to wild type, had reduced total biomass, reduced water-use efficiency, and a decreased proportion of cellulose to hemicellulose and lignin. In low nutrient conditions, TnCelB trees had increased structural carbohydrates with stable lignin values. The TnCelB line presents a viable option for poplar biomass feedstock, offering biomass comparable to wild type poplar and more efficient processing, with only mild negative phenotypes.

Natalie, Bethanie M. (ORCID:0009000843856585)↗
DOE OSTI2023

The characterization of wear-causing particles and silica sand in particular

Erodants and abradants are two types of wear-causing particles (WCP). Despite their effects on the severity and rate of wear, WCP are inadequately characterized in a surprising number of publications, especially those involving impingement erosion and three-body abrasion. That shortfall makes it difficult to correlate features of WCP with the details of worn surfaces, or to develop wear models that account for those features. It is argued that the documentation of WCP should go beyond simply reporting their composition and mean particle size. In late 1985, ASTM Committee G2 on Wear and Erosion established a task group on the characterization of WCP. At that time, image analysis was slower and less sophisticated than it is today. While that ASTM task group failed to produce a consensus standard, computerized particle characterization methods were developing in fields other than tribology, fields like geoscience, heavy sand mining, materials processing, and pharmaceuticals. A notable exception to this is ferrography, which is a widely-used diagnostic for lubricated tribosystems. In the context of dry wear, it is useful to identify which features of WCP would be beneficial to document, and to identify some techniques and scales of detail appropriate to particular tribosystems. In this paper, examples are presented for the morphological and mechanical characterization of silica sand grains, as prompted by a triboanalysis of the abrasive and erosive wear of biomass pre-processing equipment. The authors propose a minimum level of documentation for WCP, one that can enrich tribosystem analysis both in laboratory tests and field studies.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Biological Oceanography

Within the framework of global biogeochemical cycles and ocean productivity, there are two areas that will be of particular interest to biological oceanography in the 1990s. The first is the mapping in space time of the biomass and productivity of phytoplankton in the world ocean. The second area is the coupling of biological and physical processes as it affects the distribution and growth rate of phytoplankton biomass. Certainly other areas will be of interest to biological oceanographers, but these two areas are amenable to observations from satellites. Temporal and spatial variability is a regular feature of marine ecosystems. The temporal and spatial variability of phytoplankton biomass and productivity which is ubiquitous at all time and space scales in the ocean must be characterized. Remote sensing from satellites addresses these problems with global observations of mesocale (2 to 20 days, 10 to 200 km) features over a long period of time.

Abbott, M. R.↗
NASA NTRS2005

Self-dissimilarity as a High Dimensional Complexity Measure

For many systems characterized as "complex" the patterns exhibited on different scales differ markedly from one another. For example the biomass distribution in a human body "looks very different" depending on the scale at which one examines it. Conversely, the patterns at different scales in "simple" systems (e.g., gases, mountains, crystals) vary little from one scale to another. Accordingly, the degrees of self-dissimilarity between the patterns of a system at various scales constitute a complexity "signature" of that system. Here we present a novel quantification of self-dissimilarity. This signature can, if desired, incorporate a novel information-theoretic measure of the distance between probability distributions that we derive here. Whatever distance measure is chosen, our quantification of self-dissimilarity can be measured for many kinds of real-world data. This allows comparisons of the complexity signatures of wholly different kinds of systems (e.g., systems involving information density in a digital computer vs. species densities in a rain-forest vs. capital density in an economy, etc.). Moreover, in contrast to many other suggested complexity measures, evaluating the self-dissimilarity of a system does not require one to already have a model of the system. These facts may allow self-dissimilarity signatures to be used a s the underlying observational variables of an eventual overarching theory relating all complex systems. To illustrate self-dissimilarity we present several numerical experiments. In particular, we show that underlying structure of the logistic map is picked out by the self-dissimilarity signature of time series produced by that map

Wolpert, David H.↗
DOE OSTI2024

Solid–liquid separation of lignocellulosic sugars from biomass by rotating ceramic disc filtration

In many biomass conversion processes, the separation of cellulosic sugars from residual, lignin-rich solids is a critical step, and achieving high recovery yields of sugars by conventional tangential crossflow and vacuum filtration is challenged by the presence of biomass solids, which rapidly foul filters, resulting in decreased throughput. Considering the performance limitations of traditional filtration methods, dynamic filtration, which generates high shear at the membrane surface to decrease fouling, is emerging as a viable alternative for demanding solid–liquid separations. For high solids separations, there is little available information regarding the performance, limitations, and energy consumption of dynamic filtration. To that end, here we characterized the performance of a dynamic filtration module, specifically a rotating ceramic disc (RCD) filter, for the aseptic recovery of cellulosic sugars from biomass solids following pretreatment and enzymatic hydrolysis. We show how RCD rotational velocity and percent biomass solids impact the filter throughput. Additionally, we used computational fluid dynamics (CFD) simulations to estimate the shear rate at the membrane surface and to visualize hydrodynamic profiles within the module. With the combined CFD simulations and experimental results, we estimated the energy demand and operating expenses for a viable dynamic filtration system operating with a lignocellulosic feed slurry. Our results indicate that an RCD filter can achieve ≥95% recovery of sugars and produce a retentate slurry containing 12 wt% insoluble solids with low energy consumption (a 2.2-fold improvement over cross-flow filtration) and low operating costs ($\$$0.06 per kg sugars). These results show a viable path towards operationally reliable, energy efficient, and cost-effective separations of sterilized cellulosic sugars from biomass solids and highlight the potential of dynamic filtration systems for challenging solid–liquid separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2018

Multilayer Approach for Characterization of Bacterial Diversity in a Marginal Sea: From Surface to Seabed

Bacteria are the most important microorganisms in the world oceans, accounting for up to 75% of the total biomass. They are responsible for fundamental biogeochemical processes and therefore often used as ecological indicators. In this study, bacteria were quantified by flow cytometry and their diversity assessed by High Throughput Sequencing (HTS) in the southern Adriatic Sea. The most abundant bacterial groups were also quantified by qPCR. The samples were collected from the surface to the seabed over a total of 16 different depths at four stations during the late winter BIOTA (BIO-Tracing Adriatic water masses) cruise conducted in March 2016. The investigated area showed unusual water mass properties and was characterized by a shallow mixed layer, which differed from the usual winter convection conditions, typical of middle-altitude ecosystems and important for the seasonal picoplankton dynamics of this area. Heterotrophic bacteria were separated into HNA (relative High Nucleic Acid content) and LNA (Low Nucleic Acid content) subpopulations with abundances up to 1.8×10(exp 5) and 8.8×10(exp 5) cells/mL, respectively. HNA dominated at offshore stations reaching their maximum at depths below the euphotic zone. The bacterial community was dominated by Alphaproteobacteria, accounting for greater than 40% of the total sequence reads and were mainly represented by the SAR11 clade (90.84%), followed by Marinimicrobia (18% of the total sequence reads), mainly represented by clade SAR406 (8.44%). Distinctive bacterial groups were found in the euphotic layer (Bacteroidetes and Actinobacteria) and aphotic layer samples (Deltaproteobacteria, Marinimicrobia, Chloroflexi, Acidobacteria and Planctomycetes). Results of the qPCR analyses further confirmed HTS results with highest abundances obtained for Alphaproteobacteria, followed by Gammaproteobacteria and Bacteroidetes. The adopted multiple approach, combining different molecular tools, critically supported by optics and flow cytometry, reveal changes in the bacterial assemblages during the unusual thermohaline conditions observed in 2016 in the southern Adriatic Sea.

Southern Adriatic Sea↗
DOE OSTI2023

Functional characterization and regulatory modeling of lignocellulose deconstruction in the saprophytic bacterium Cellvibrio japonicus (Final Technical Report)

The goal of this project was to establish a fundamental systems-level model of lignocellulose deconstruction by saprophytic soil bacteria while simultaneously identifying and characterizing novel enzymes that can be used for applied bioenergy technologies. This project was significant because it elevated our mechanistic and regulatory understanding of bacterial plant biomass degradation and led to technologies to enable bottlenecks in biofuel production R&D. Furthermore, the completed work was novel because it integrated in vivo, in vitro, and in silico approaches with bioenergy-relevant substrates. We identified the required enzymes for lignocellulose degradation and mechanisms of regulation through a combination of transcriptomic profiling (RNAseq), enzymatic analysis, the functional characterization of mutants, and modeling of the regulatory networks used to detect and degrade lignocellulose. This project employed the lignocellulose-degrading bacterium Cellvibrio japonicus to dissect the functional properties and underlying regulatory networks saprophytic bacteria use to depolymerize and utilize lignocellulose. There were four Objectives to this project, the specific metrics of which are summarized in this report.

09 BIOMASS FUELS↗
DOE OSTI2023

Emission factors of industrial boilers burning biomass-derived fuels

Boilers are combustion devices that provide process heat and are integral to many industrial facilities. Historically, outside of the pulp and paper industry, most boilers burned fossil fuels, although interest in decarbonization has been leading to an increased use of renewable fuels in boilers. These boilers, including those in the biorefineries, are often large sources of air pollutant emissions, and the characterization of these emissions is critical to obtaining air permits and ensuring protection of the surrounding air quality. Several industrial boilers and new biorefineries allow utilization of biomass-derived fuels (e.g. wastewater sludge, lignin, etc.) produced during their operation as a fuel for the boiler to meet process energy needs. However, there is limited empirical data on emission factors for the burning of unconventional fuels, such as solid-gas mixtures containing biomass residues. To fill this gap, we carry out a comprehensive data survey, collecting information on emission factors for boilers burning either a single or a mixture of solid and gaseous biomass-derived fuels. We review multiple hard-to-obtain and unconventional data sources, such as air permit applications, stack test data, and industry-sponsored data collection efforts, to compile emission factors for biomass-derived fuels. We then compare this data with wood residue emission factors from the U.S. Environmental Protection Agency’s AP-42 emission factor database. Our results indicate that the emission factors for boilers burning unconventional fuels vary widely depending on the fuel composition, boiler type, and fuel characteristics. Overall, we find that median emission factors of selected biomass-derived fuels are typically lower than those of wood residue boilers in AP-42. The information collected herein could be useful to permitting agencies and industries utilizing boilers who may want to reduce the carbon impact of their facilities by combusting biomass-derived wastes for process energy needs, for more accurate emission estimation for permitting.

09 BIOMASS FUELS↗
DOE OSTI2023

Biostimulation of Salicornia europaea L. crops with plant growth-promoting bacteria in laboratory and field conditions: effects on growth and metabolite profile

Abstract Aim The objective of the work was to assess the effect of biostimulation with selected plant growth-promoting bacteria on growth and metabolite profile of Salicornia europaea. Methods and results Salicornia europaea seeds were inoculated with different combinations of plant growth-promoting bacteria Brevibacterium casei EB3, Pseudomonas oryzihabitans RL18, and Bacillus aryabhattai SP20. Plants germinated from inoculated seeds were grown either in laboratory conditions or in a saline crop field. Fresh and dry weight were determined at the end of the experiment, for biomass quantification. The microbiological quality of fresh shoots for human consumption as salad greens was assessed, and the persistence of the inoculated strains in the plant rhizosphere was confirmed by next-generation sequencing (Illumina) of the 16S rDNA gene. The primary metabolite profile of biostimulated plants was characterized by GC–TOF-MS. In laboratory conditions, inoculation with the two strains Br. casei EB3 and Ps. oryzihabitans RL18 caused the most significant increase in biomass production (fresh and dry weight), and caused a shift in the central metabolic pathways of inoculated plants toward amino acid biosynthesis. In the field experiment, no significant biostimulation effect was detected with any of the tested inoculants. Seed inoculation had no significant effect on the microbiological quality of the edible parts. The persistence of inoculants was confirmed in both experiments. Conclusions Manipulation of the plant microbiome can trigger primary metabolic reconfiguration and modulate the plant metabolism while promoting plant growth.

Ferreira, Maria J.↗
DOE OSTI2021

THF co-solvent pretreatment prevents lignin redeposition from interfering with enzymes yielding prolonged cellulase activity

Background: Conventional aqueous dilute sulfuric acid (DSA) pretreatment of lignocellulosic biomass facilitates hemicellulose solubilization and can improve subsequent enzymatic digestibility of cellulose to fermentable glucose. However, much of the lignin after DSA pretreatment either remains intact within the cell wall or readily redeposits back onto the biomass surface. This redeposited lignin has been shown to reduce enzyme activity and contribute to rapid enzyme deactivation, thus, necessitating significantly higher enzyme loadings than deemed economical for biofuel production from biomass. Results: In this study, we demonstrate how detrimental lignin redeposition on biomass surface after pretreatment can be prevented by employing Co-solvent Enhanced Lignocellulosic Fractionation (CELF) pretreatment that uses THF–water co-solvents with dilute sulfuric acid to solubilize lignin and overcome limitations of DSA pretreatment. We first find that enzymatic hydrolysis of CELF-pretreated switchgrass can sustain a high enzyme activity over incubation periods as long as 5 weeks with enzyme doses as low as 2 mg protein/g glucan to achieve 90% yield to glucose. A modified Ninhydrin-based protein assay revealed that the free-enzyme concentration in the hydrolysate liquor, related to enzyme activity, remained unchanged over long hydrolysis times. DSA-pretreated switchgrass, by contrast, had a 40% drop in free enzymes in solution during incubation, providing evidence of enzyme deactivation. Furthermore, measurements of enzyme adsorption per gram of lignin suggested that CELF prevented lignin redeposition onto the biomass surface, and the little lignin left in the solids was mostly integral to the original lignin–carbohydrate complex (LCC). Scanning electron micrographs and NMR characterization of lignin supported this observation. Conclusions: Enzymatic hydrolysis of solids from CELF pretreatment of switchgrass at low enzyme loadings was sustained for considerably longer times and reached higher conversions than for DSA solids. Analysis of solids following pretreatment and enzymatic hydrolysis showed that prolonged cellulase activity could be attributed to the limited lignin redeposition on the biomass surface making more enzymes available for hydrolysis of more accessible glucan.

09 BIOMASS FUELS↗
DOE OSTI2023

Validation of a metabolite–GWAS network for Populus trichocarpa family 1 UDP-glycosyltransferases

Metabolite genome-wide association studies (mGWASs) are increasingly used to discover the genetic basis of target phenotypes in plants such as Populus trichocarpa , a biofuel feedstock and model woody plant species. Despite their growing importance in plant genetics and metabolomics, few mGWASs are experimentally validated. Here, we present a functional genomics workflow for validating mGWAS-predicted enzyme–substrate relationships. We focus on uridine diphosphate–glycosyltransferases (UGTs), a large family of enzymes that catalyze sugar transfer to a variety of plant secondary metabolites involved in defense, signaling, and lignification. Glycosylation influences physiological roles, localization within cells and tissues, and metabolic fates of these metabolites. UGTs have substantially expanded in P. trichocarpa , presenting a challenge for large-scale characterization. Using a high-throughput assay, we produced substrate acceptance profiles for 40 previously uncharacterized candidate enzymes. Assays confirmed 10 of 13 leaf mGWAS associations, and a focused metabolite screen demonstrated varying levels of substrate specificity among UGTs. A substrate binding model case study of UGT-23 rationalized observed enzyme activities and mGWAS associations, including glycosylation of trichocarpinene to produce trichocarpin, a major higher-order salicylate in P. trichocarpa. We identified UGTs putatively involved in lignan, flavonoid, salicylate, and phytohormone metabolism, with potential implications for cell wall biosynthesis, nitrogen uptake, and biotic and abiotic stress response that determine sustainable biomass crop production. Our results provide new support for in silico analyses and evidence-based guidance for in vivo functional characterization.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1989

Utilization of non-conventional systems for conversion of biomass to food components

The potential use of micro-algae in yielding useful macronutrients for the CELSS is investigated. Algal proteins were isolated and characterized from green algae (Scenedesmus obliquus) grown under controlled conditions. The RNA and DNA contents were determined, and methodology for reduction of the nucleic acid content to acceptable levels developed. Lipid extraction procedures using supercritical fluids were tailored to removal of undesirable lipids and pigments. Initial steps toward preparation of model foods for potential use in the CELSS were taken. The goal was to fabricate food products which contain isolated algal macronutrients such as proteins and lipids and also some components derived from higher plants including wheat flour, soy flour, potato powder (flakes), soy oil, and corn syrup.

Karel, M.↗
NASA NTRS2013

Meteorological Controls on Biomass Burning During Santa Ana Events in Southern California

Fires occurring during Santa Ana (SA) events in southern California are driven by extreme fire weather characterized by high temperatures, low humidities, and high wind speeds. We studied the controls on burned area and carbon emissions during two intensive SA burning periods in 2003 and 2007. We therefore used remote sensing data in parallel with fire weather simulations of the Weather and Regional Forecast model. Total carbon emissions were approximately 1800 gigagrams in 2003 and 900 gigagrams in 2007, based on a daily burned area and a fire emission model that accounted for spatial variability in fuel loads and combustion completeness. On a regional scale, relatively strong positive correlations were found between the daily Fosberg fire weather index and burned area/emissions (probability is less than 0.01). Our analysis provides a quantitative assessment of relationships between fire activity and weather during severe SA fires in southern California.

Santa Ana (SA)↗
NASA NTRS2003

Individual Aerosol Particles from Biomass Burning in Southern Africa: Compositions and Size Distributions of Carbonaceous Particles - 1

Individual aerosol particles in smoke plumes from biomass fires and in regional hazes in southern Africa were studied using analytical transmission electron microscopy (TEM), which allowed detailed characterization of carbonaceous particle types in smoke and determination of changes in particle properties and concentrations during smoke aging. Based on composition, morphology, and microstructure, three distinct types of carbonaceous particles were present in the smoke: organic particles with inorganic (K-salt) inclusions, tar ball particles, and soot. The relative number concentrations of organic particles were largest in young smoke, whereas tar balls were dominant in a slightly aged (1 hour) smoke from a smoldering fire. Flaming fires emitted relatively more soot particles than smoldering fires, but soot was a minor constituent of all studied plumes. Further aging caused the accumulation of sulfate on organic and soot particles, as indicated by the large number of internally mixed organic/sulfate and soot/sulfate particles in the regional haze. Externally mixed ammonium sulfate particles dominated in the boundary layer hazes, whereas organic/sulfate particles were the most abundant type in the upper hazes. Apparently, elevated haze layers were more strongly affected by biomass smoke than those within the boundary layer. Based on size distributions and the observed patterns of internal mixing, we hypothesize that organic and soot particles are the cloud-nucleating constituents of biomass smoke aerosols. Sea-salt particles dominated in the samples taken in stratus clouds over the Atlantic Ocean, off the coast of Namibia, whereas a distinct haze layer above the clouds consisted of aged biomass smoke particles.

Posfai, Mihaly↗
DOE OSTI2020

Multi-Temporal Predictive Modelling of Sorghum Biomass Using UAV-Based Hyperspectral and LiDAR Data

High-throughput phenotyping using high spatial, spectral, and temporal resolution remote sensing (RS) data has become a critical part of the plant breeding chain focused on reducing the time and cost of the selection process for the “best” genotypes with respect to the trait(s) of interest. In this paper, the potential of accurate and reliable sorghum biomass prediction using visible and near infrared (VNIR) and short-wave infrared (SWIR) hyperspectral data as well as light detection and ranging (LiDAR) data acquired by sensors mounted on UAV platforms is investigated. Predictive models are developed using classical regression-based machine learning methods for nine experiments conducted during the 2017 and 2018 growing seasons at the Agronomy Center for Research and Education (ACRE) at Purdue University, Indiana, USA. The impact of the regression method, data source, timing of RS and field-based biomass reference data acquisition, and the number of samples on the prediction results are investigated. R2 values for end-of-season biomass ranged from 0.64 to 0.89 for different experiments when features from all the data sources were included. Geometry-based features derived from the LiDAR point cloud to characterize plant structure and chemistry-based features extracted from hyperspectral data provided the most accurate predictions. Evaluation of the impact of the time of data acquisition during the growing season on the prediction results indicated that although the most accurate and reliable predictions of final biomass were achieved using remotely sensed data from mid-season to end-of-season, predictions in mid-season provided adequate results to differentiate between promising varieties for selection. The analysis of variance (ANOVA) of the accuracies of the predictive models showed that both the data source and regression method are important factors for a reliable prediction; however, the data source was more important with 69% significance, versus 28% significance for the regression method.

09 BIOMASS FUELS↗