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DOE OSTI2022

Sulfur Geochemistry Destabilizes Population Oscillations of Wild Rice ( Zizania palustris )

Abstract Elevated inputs of sulfate to freshwater systems can increase sulfide concentrations in anoxic soils and subsequently destabilize aquatic plant populations, but the interactions between sulfate, other geochemical cycles, and interannual plant population cycles are poorly understood. Increased sulfate loading increases mineralization of nitrogen from litter, but the sulfide produced during this process can limit nitrogen uptake by plants. In some cases, iron may mitigate sulfide's impacts on plants by precipitating iron sulfide. We examined the interannual effects of sulfate loading on mesocosm populations of wild rice, an emergent aquatic plant that undergoes population oscillations and is sensitive to sulfide. Using experimental mesocosms with self‐perpetuating populations, we investigated how population dynamics respond to manipulations of surface water sulfate (10 mg L −1 or 300 mg L −1 ), sediment iron (4.3 mg g −1 or 10.9 mg g −1 dry weight), and shoot litter (present or removed). Populations exposed to constant 10 mg L −1 sulfate concentrations had stable biomass oscillations of approximately 3‐year periods, consistent with previous studies that demonstrated litter‐driven oscillations in nitrogen availability. Populations exposed to 300 mg L −1 sulfate concentrations produced fewer and smaller seeds and declined to extinction in 6 years or less. We did not find a strong effect of iron loading or litter removal on wild rice biomass or seed production. Our observations show the potential of elevated surface water sulfate to rapidly destabilize wild rice populations under varying iron and organic carbon concentrations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Enhancing organic matter removal, product recovery, and hydrogen generation from fermentation wastewater

Existing ethanol biorefineries produce billions of gallons of wastewater (stillage) that must be treated extensively prior to discharge or concentrated in an energy intense evaporation step to produce animal feed as a value-added bioproduct. Yeasts and filamentous fungi were screened for growth and reduction of soluble organic compounds, carbohydrates, and protein from stillage to identify species capable of rapidly concentrating organic compounds into readily separable biomass in an attempt to concentrate the product using a much more efficient centrifugation step. Yeasts amenable to production of biomass derived products including bio-oils (Yarrowia lipolytica and Rhodotorula pallida), chitosan (Aspergillus niger) and animal feed (Cyberlindnera jadinii) were identified as well as microbes capable of efficient production of small organic acids with applications as bioderived polymers including 3-hydroxypropionic acid (engineered A. niger) and lactic acid using a co-culture of Debaryomyces udenii and Lactobacillus pentosus. The filamentous fungus A. niger eliminated all specifically measured soluble organics (glycerol, acetate, lactate, ethanol, and citrate) in under 48 hours and reduced total soluble protein content by 46% and total carbohydrate content by 83% within 96 hours, the greatest reduction in organic content observed. During this process an A. niger strain engineered to produce 3-hydroxypropionic acid achieved a yield of 0.35 C-mol 3HP / C-mol non-protein organics consumed at an overall rate of 0.09 g/Lh in unmodified stillage without pH control. Stillage treated by the fodder yeast C. jadinii as well as stillage containing acetic or lactic acid was found to be most suitable for growth by electrogenic bacteria with applications in production of electricity or hydrogen from wastewater. This work establishes fungal and bacterial strains appropriate for biological treatment of stillage to produce biomass derived products, soluble commodity chemicals, energy, and treated water to reduce the energy intensity and improve the economics of ethanol biorefineries.

09 BIOMASS FUELS↗

NASA NTRS2008

Deep-Sea Hydrothermal-Vent Sampler

An apparatus is being developed for sampling water for signs of microbial life in an ocean hydrothermal vent at a depth of as much as 6.5 km. Heretofore, evidence of microbial life in deep-sea hydrothermal vents has been elusive and difficult to validate. Because of the extreme conditions in these environments (high pressures and temperatures often in excess of 300 C), deep-sea hydrothermal- vent samplers must be robust. Because of the presumed low density of biomass of these environments, samplers must be capable of collecting water samples of significant volume. It is also essential to prevent contamination of samples by microbes entrained from surrounding waters. Prior to the development of the present apparatus, no sampling device was capable of satisfying these requirements. The apparatus (see figure) includes an intake equipped with a temperature probe, plus several other temperature probes located away from the intake. The readings from the temperature probes are utilized in conjunction with readings from flowmeters to determine the position of the intake relative to the hydrothermal plume and, thereby, to position the intake to sample directly from the plume. Because it is necessary to collect large samples of water in order to obtain sufficient microbial biomass but it is not practical to retain all the water from the samples, four filter arrays are used to concentrate the microbial biomass (which is assumed to consist of particles larger than 0.2 m) into smaller volumes. The apparatus can collect multiple samples per dive and is designed to process a total volume of 10 L of vent fluid, of which most passes through the filters, leaving a total possibly-microbe-containing sample volume of 200 mL remaining in filters. A rigid titanium nose at the intake is used for cooling the sample water before it enters a flexible inlet hose connected to a pump. As the water passes through the titanium nose, it must be cooled to a temperature that is above a mineral-precipitation temperature of 100 C but below the upper working temperature (230 C) of switching valves and tubes in the apparatus. The sample water then passes into a manifold tube, from whence the switching valves can direct the water through either a bypass tube or any one of the filter arrays, without contamination from a previous sample. Each filter array consists of series of filters having pore sizes decreasing in the direction of flow: 90-, 60-, 15-, and 7-micron prefilters and a large-surface-area 0.2-micron collection filter. All the filter taps are located between the intake and the bypass tube so that each time the bypass tube is used, the entire manifold tube is flushed as well.

Behar, Alberto E.↗

DOE OSTI2025

Understanding the impacts of inorganic species in woody biomass for preprocessing and pyrolysis–A review

Woody biomass represents an abundant resource for sustainable biofuels, biochemicals, and bioproducts. Technologies for converting woody biomass have been established for decades, and research consistently highlights the critical role of inorganic species and ash plays in feedstock handling and conversion processes, including equipment plugging, corrosion, and catalyst deactivation. A thorough understanding of the variability, transport behavior, and downstream impact of inorganic species in woody biomass is essential for defining feedstock quality specifications and developing effective management strategies for conversion processes. This review compiles critical information in five main sections: 1) inorganic species concentration in woody biomass, based on anatomical fractions and their sources of variability; 2) technique features for quantifying inorganic elemental chemical analysis; 3) impacts of inorganic species on biomass preprocessing; 4) impacts of inorganic species on pyrolysis, and 5) mitigation strategies. Additionally, this review explores future challenges and opportunities in addressing the impacts of inorganic species on biomass quality. These insights aim to support the sustainable development of the biomass-to-bioenergy pipeline and ensure high-quality lignocellulosic feedstocks for efficient downstream conversions. The findings offer valuable guidance to policy makers, industry stakeholders, and researchers in developing effective strategies for managing inorganic species in woody biomass and fostering the sustainable processes for lignocellulosic biorefineries.

09 BIOMASS FUELS↗

DOE OSTI2022

Aerosol size distribution changes in FIREX-AQ biomass burning plumes: the impact of plume concentration on coagulation and OA condensation/evaporation

Abstract. The evolution of organic aerosol (OA) and aerosol size distributions within smoke plumes is uncertain due to the variability in rates of coagulation and OA condensation/evaporation between different smoke plumes and at different locations within a single plume. We use aircraft data from the FIREX-AQ campaign to evaluate differences in evolving aerosol size distributions, OA, and oxygen to carbon ratios (O:C) between and within smoke plumes during the first several hours of aging as a function of smoke concentration. The observations show that the median particle diameter increases faster in smoke of a higher initial OA concentration (>1000 µg m−3), with diameter growth of over 100 nm in 8 h – despite generally having a net decrease in OA enhancement ratios – than smoke of a lower initial OA concentration (<100 µg m−3), which had net increases in OA. Observations of OA and O:C suggest that evaporation and/or secondary OA formation was greater in less concentrated smoke prior to the first measurement (5–57 min after emission). We simulate the size changes due to coagulation and dilution and adjust for OA condensation/evaporation based on the observed changes in OA. We found that coagulation explains the majority of the diameter growth, with OA evaporation/condensation having a relatively minor impact. We found that mixing between the core and edges of the plume generally occurred on timescales of hours, slow enough to maintain differences in aging between core and edge but too fast to ignore the role of mixing for most of our cases.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Fine Root and Soil Organic Carbon Depth Distributions are Inversely Related Across Fertility and Rainfall Gradients in Lowland Tropical Forests

Humid tropical forests contain some of the largest soil organic carbon (SOC) stocks on Earth. Much of this SOC is in subsoil, yet variation in the distribution of SOC through the soil profile remains poorly characterized across tropical forests. We used a correlative approach to quantify relationships among depth distributions of SOC, fine root biomass, nutrients and texture to 1 m depths across 43 lowland tropical forests in Panama. The sites span rainfall and soil fertility gradients, and these are largely uncorrelated for these sites. We used fitted b parameters to characterize depth distributions, where b is a numerical index based on an asymptotic relationship, such that larger b values indicate greater concentrations of root biomass or SOC at depth in the profile. Root b values ranged from 0.82 to 0.95 and were best predicted by soil pH and extractable potassium (K) stocks. For example, the three most acidic (pH < 4) and Kpoor (< 20 g K m -2 ) soils contained 76 ± 5% of fine root biomass from 0 to 10 cm depth, while the three least acidic (pH > 6.0) and most K-rich (> 50 g K m -2 ) soils contained only 41 ± 9% of fine root biomass at this depth. Root b and SOC b values were inversely related, such that a large fine root biomass in surface soils corresponded to large SOC stocks in subsoils (50–100 cm). SOC b values were best predicted by soil pH and base cation stocks, with the three most base-poor soils containing 34 ± 8% of SOC from 50 to 100 cm depth, and the three most base-rich soils containing just 9 ± 2% of SOC at this depth. Nutrient depth distributions were not related to Root b or SOC b values. Here, these data show that large surface root biomass stocks are associated with large subsoil C stocks in strongly weathered tropical soils. Further studies are required to evaluate why this occurs, and whether changes in surface root biomass, as may occur with global change, could in turn influence SOC storage in tropical forest subsoils.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Comparative performance and technoeconomic analyses of two microalgae harvesting systems evaluated at a commercially relevant scale

Using a commercially scalable system designed for processing thousands of liters a day, here we evaluated the factors that affected the performance, energy consumption and capital/operating costs of both flocculation-based and filtration-based algal harvesting systems over a 16 month period. Coagulation efficiency was the primary driver of harvest efficiency in the flocculation-based method, while cell lysis was important for the filtration-based method. Culture (algae) age differentially influenced harvest efficiency through changes in cell fragility and stickiness. The average energy consumption of the flocculation-based method was 0.389 kWh/m 3 , while that for the filtration-based method was 4.343 kWh/m 3 . The average harvesting cost of the filtration-based method was 5.35 $\$$/m 3 , while for flocculation-based method it was 4.52 $\$$/m 3 . The concentration factor of filtration-based and flocculation-based method were 770–1086 and 407–448, respectively. For both harvesting methods, labor costs dominated and ranged from 55.84%–67.94% of total cost. Further system automation is a potential method to lower the harvesting cost. The filtration-based harvesting method could produce a better quality of algal biomass with higher concentration factors and less ash content, but needed more energy input, as compared with a flocculation-based method. This study highlights the importance of algal culture status to successful harvesting, and it also provides insight into developing more efficient harvesting technology with lower energy and capital cost.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1992

Interannual variability in phytoplankton blooms observed in the northwestern Arabian Sea during the southwest monsoon

Interannual changes in the strength and seasonal evolution of the 1979 through 1982 surface-level southwest monsoon winds are related to variations in the summer phytoplankton bloom of the northwestern Arabian Sea by synthesis of satellite ocean-color remote sensing with analysis of in-situ hydrographic and meteorological data sets. The 1979-1981 southwest monsoon phytoplankton blooms in the northwest Arabian Sea peaked during August-September, extended from the Omani coast to about 6 E, and appeared to lag the development of open-sea upwelling by at least 1 month. In all 3 years the bloom was driven by spatially distinct upward nutrient fluxes to the euphotic zone forced by the physical processes of coastal upwelling and offshore Ekman pumping. Coastal upwelling was evident from May through September, yielded the most extreme concentrations of phytoplankton biomass, and along the Omani coast was limited in its impact on upper ocean biological variability to the continental shelf. Ekman pumping stimulated the development of a broad open-ocean component of the southwest monsoon phytoplankton bloom oceanward of the Omani shelf. Phytoplankton biomass on the Omani continental shelf was increased during both the early and late phases of the 1980 southwest monsoon due to stronger coastal upwelling under the most intense southwesterly winds of the four summers investigated. Diminished coastal upwelling during the early phase of the weak 1982 southwest monsoon resulted in a coastal bloom that reached a mean phytoplankton-pigment concentration that was 28 percent of that seen in 1980. The lack of a strong regional northwestern Arabian Sea bloom in late summer 1982 is attributed to the development of persistent, shallow temperature stratification that rendered Ekman pumping less effective in driving upward nutrient fluxes.

Brock, John C.↗

DOE OSTI2021

Predictability of Seawater DMS During the North Atlantic Aerosol and Marine Ecosystem Study (NAAMES)

This work presents an overview of a unique set of surface ocean dimethylsulfide (DMS) measurements from four shipboard field campaigns conducted during the North Atlantic Aerosol and Marine Ecosystem Study (NAAMES) project. Variations in surface seawater DMS are discussed in relation to biological and physical observations. Results are considered at a range of timescales (seasons to days) and spatial scales (regional to sub-mesoscale). Elevated DMS concentrations are generally associated with greater biological productivity, although chlorophyll a (Chl) only explains a small fraction of the DMS variability (15%). Physical factors that determine the location of oceanic temperature fronts and depth of vertical mixing have an important influence on seawater DMS concentrations during all seasons. The interplay of biomass and physics influences DMS concentrations at regional/seasonal scales and at smaller spatial and shorter temporal scales. Seawater DMS measurements are compared with the global seawater DMS climatology and predictions made using a recently published algorithm and by a neural network model. The climatology is successful at capturing the seasonal progression in average seawater DMS, but does not reproduce the shorter spatial/temporal scale variability. The input terms common to the algorithm and neural network approaches are biological (Chl) and physical (mixed layer depth, photosynthetically active radiation, seawater temperature). Both models predict the seasonal North Atlantic average seawater DMS trends better than the climatology. However, DMS concentrations tend to be under-predicted and the episodic occurrence of higher DMS concentrations is poorly predicted. The choice of climatological seawater DMS product makes a substantial impact on the estimated DMS flux into the North Atlantic atmosphere. These results suggest that additional input terms are needed to improve the predictive capability of current state-of-the-art approaches to estimating seawater DMS.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2017

How Accurately Do Maize Crop Models Simulate the Interactions of Atmospheric CO2 Concentration Levels With Limited Water Supply on Water Use and Yield?

This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration [CO2] on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thunen Institute in Braunschweig, Germany (Manderscheid et al. 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50 percent of models within a range of plus/minus 1 Mg ha(exp. -1) around the mean. The bias of the median of the 21 models was less than 1 Mg ha(exp. -1). However under water deficit in one of the two years, the models captured only 30 percent of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase.

grain number↗

DOE OSTI2022

Bioproducts from high-protein algal biomass: An economic and environmental sustainability review and risk analysis

This report has High-protein algal biomass as an important bio-commodity that has the potential to provide a new source of sustainable protein products. Herein is a critical review that identifies 1) the most relevant sustainability findings related to the processing of proteinaceous algal biomass to higher value protein products and 2) the potential pathways to improve life cycle assessment (LCA) and techno-economic analysis (TEA) metrics, including life-cycle carbon dioxide equivalent (CO 2 eq), life cycle energy, and minimum selling price (MSP) of these products. The critical review of the literature revealed a large variation in model input parameters relating to these metrics. Therefore, a Monte Carlo analysis was conducted to assess the risk associated with these input variations. To understand the uncertainties that propagate into high-protein algae to products’ systems, we reviewed more than 20 state-of-the-art unit operations for algal biomass processing., including cell disruption, protein solubilization, protein precipitation and purification, and protein concentration. We evaluated displacement of proteinaceous products by algal-bioproducts, including ruminant feed, aquaculture feed, protein tablets, and biopolymers and biopolyesters, with prices in the market ranging from 1.9 to 120 $\$$ kg -1 protein. This review realized that the MSP of ruminant and non-ruminant feed ranges from 0.65±0.56 to 2.9±1.1 $\$$ kg -1 protein, and bioplastics’ MSP ranges from 0.97 to 7.0 $\$$ kg -1 protein. Regarding LCA metrics, there is limited research on life cycle energy in proteinaceous biomass concentration and bioproduct systems, reported at 32.7 MJ kg protein -1 , for animal feed displacement. Animal feed emissions in the literature report negative fluxes, representing environmental benefits, as low as -3.7 kgCO 2 eq kg -1 protein and positive fluxes, i.e., global warming potential, as high as 12.8 kgCO 2 eq kg -1 protein. There is limited research on bioplastics life cycle emissions reported at 0.6 kgCO 2 eq kg -1 protein. In general, the studies to date of algae-derived protein bioproducts showed similar life cycle emissions to soybean meals, nylon, polymers, and polystyrenes. Our risk analysis realized that more than 50% of scenarios can result in negative-net life cycle CO 2 eq emissions. This review and risk analysis assess and demonstrate the scenarios that improve economic and environmental sustainability metrics in high-protein algal bioproducts systems.

09 BIOMASS FUELS↗

DOE OSTI2025

Data for Identifying the best high-biomass sorghum hybrids based on biomass yield potential and feedstock quality affected by nitrogen fertility management under various environments

Data were collected from agronomy fields in Urbana and Ewing, IL, during the 2022 and 2023 growing seasons. The dataset includes dry biomass yield, nitrogen, phosphorus, and potassium concentrations and removals, and chemical composition elements (cellulose, hemicellulose, lignin, and soluble fractions) for 13 high-biomass sorghum hybrids. data_sharing.xlsx contains 20 columns and 104 rows. Below is the explanation of all variables in the file: Year: 2022; 2023 Location: Urbana, IL; Ewing, IL N rate (kg-N/ha): 0; 112 Hybrid #: H1-H13 Pedigree: Pedigree for 13 hybrids Dry biomass yield (Mg/ha): Aboveground dry biomass yield N (g/kg): Nitrogen concentration in plant tissue P (g/kg): Phosphorus concentration in plant tissue K (g/kg): Potassium concentration in plant tissue N (kg/ha): Nitrogen removal by aboveground biomass P (kg/ha): Phosphorus removal by aboveground biomass K (kg/ha): Potassium removal by aboveground biomass Cellulose (g/kg): Cellulose concentration in plant tissue Hemicellulose (g/kg): Hemicellulose concentration in plant tissue Lignin (g/kg): Lignin concentration in plant tissue Soluble (g/kg): Soluble concentration in plant tissue Cellulose (Mg/ha): Cellulose content in aboveground biomass Hemicellulose (Mg/ha): Hemicellulose content in aboveground biomass Lignin (Mg/ha): Lignin content in aboveground biomass Soluble (Mg/ha): Soluble content in aboveground biomass

environmental adaptability↗

DOE OSTI2021

Chitin extracted from various biomass sources: It's not the same

Here this study demonstrates the use of ionic liquids to successfully extract chitin from different biomass sources and the utilization of the resulting chitins to prepare monofilament fibers. Chitin was extracted from five different biomass sources (processed and raw shrimp shell, crab and lobster shell, and fly larvae) using the ionic liquid (IL) 1-ethyl-3-methylimidazolium acetate ([C 2 mim][OAc]). While processed and raw shrimp shell yielded chitin of high purity in quantitative yield, crab and lobster shell resulted in lower yields of chitin. Fly larva provided chitin severely contaminated with proteins. Each extracted chitin was re-dissolved in the same IL and dry wet jet spun into monofilament fibers to determine any trends in mechanical properties vs. biomass source. The concentration needed to spin fibers was not consistent and had to be adjusted individually for each type of chitin obtained. Chitin from raw shrimp shell produced the strongest fibers, while the chitin from the crab and lobster produced weaker fibers, although, the latter were twice as elastic. The use of fly larvae led to the weakest and least elastic fibers.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

EcoBOT: an AI/ML enabled automated phenotyping capability for model plants

Introduction: Advances in automation and AI/ML offer new opportunities for plant science, including design, modeling, and analysis. This study aimed to develop an automated platform for researching small model plants under axenic conditions and integrate it with AI/ML tools. Methods: The EcoBOT platform was developed, which consists of sterile containers (EcoFABs) for growing plants and imaging for monitoring plant growth and health. Brachypodium distachyon was grown on the EcoBOT, and its response to nutrient limitation and copper stress was evaluated. Results: The results showed that Brachypodium distachyon grown in the EcoBOT maintained sterility and responded to nutrient limitation and copper stress. Analysis of over 6,500 root and shoot images revealed varying sensitivity and response rates to copper. Bayesian Optimization was used to improve model accuracies relating copper concentrations to plant biomass via sequential experiments, resulting in a >30% improvement. Discussion: The findings of this study demonstrate the potential of the EcoBOT platform for researching plant responses to environmental factors. Future experiments could focus on relating other chemical stresses and microbial interactions to create generalized models of plant responses.

AI image analysis↗

DOE OSTI2021

Vertical profiles of trace gas and aerosol properties over the eastern North Atlantic: variations with season and synoptic condition

Abstract. Because of their extensive coverage, marine low clouds greatly impact the global climate. Presently, the response of marine low clouds to the changes in atmospheric aerosols remains a major source of uncertainty in climate simulations. One key contribution to this large uncertainty derives from the poor understanding of the properties and processes of marine aerosols under natural conditions and the perturbation by anthropogenic emissions. The eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer (MBL) clouds, where cloud albedo and precipitation are highly susceptible to perturbations in aerosol properties. Here we examine the key processes that drive the cloud condensation nuclei (CCN) population in the MBL using comprehensive characterizations of aerosol and trace gas vertical profiles during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. During ACE-ENA, a total of 39 research flights were conducted in the Azores: 20 during summer 2017 and 19 during winter 2018. During summer, long-range-transported aerosol layers were periodically observed in the lower free troposphere (FT), leading to elevated FT CCN concentrations (NCCN). Both biomass burning and pollution from North America contribute to submicron aerosol mass in these layers, with pollution likely the dominant contributor. In contrast, long-range transported continental emissions have a much weaker influence on the aerosol properties in the ENA during the winter season. While the entrainment of FT air is a major source of particle number in the MBL for both seasons, on average it does not serve as a direct source of CCN in the MBL because the average FT NCCN is the same or even lower than that in the MBL. The particle number flux due to FT entrainment is dominated by pre-CCN (particles that are too small to form cloud droplets under typical conditions, i.e., particles with sizes below the Hoppel minimum) due to the elevated Npre-CCN in the lower FT. Once these pre-CCN are entrained into the MBL, they can grow and reach CCN size range through condensational growth, representing an indirect and major source of MBL CCN in the ENA. The impact of synoptic conditions on the aerosol properties is examined. Under pre-front and post-front conditions, shallow convective activity often leads to a deep and decoupled boundary layer. Coalescence scavenging and evaporation of drizzle below clouds lead to reduced NCCN and larger accumulation-mode particle sizes in the upper cloud-containing decoupled layer, indicating that surface measurements overestimate the NCCN relevant to the formation of MBL clouds under decoupled conditions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2014

The Role of Phytoplankton Dynamics in the Seasonal and Interannual Variability of Carbon in the Subpolar North Atlantic - a Modeling Study

We developed an ecosystem/biogeochemical model system, which includes multiple phytoplankton functional groups and carbon cycle dynamics, and applied it to investigate physical-biological interactions in Icelandic waters. Satellite and in situ data were used to evaluate the model. Surface seasonal cycle amplitudes and biases of key parameters (DIC, TA, pCO2, air-sea CO2 flux, and nutrients) are significantly improved when compared to surface observations by prescribing deep water values and trends, based on available data. The seasonality of the coccolithophore and "other phytoplankton" (diatoms and dinoflagellates) blooms is in general agreement with satellite ocean color products. Nutrient supply, biomass and calcite concentrations are modulated by light and mixed layer depth seasonal cycles. Diatoms are the most abundant phytoplankton, with a large bloom in early spring and a secondary bloom in fall. The diatom bloom is followed by blooms of dinoflagellates and coccolithophores. The effect of biological changes on the seasonal variability of the surface ocean pCO2 is nearly twice the temperature effect, in agreement with previous studies. The inclusion of multiple phytoplankton functional groups in the model played a major role in the accurate representation of CO2 uptake by biology. For instance, at the peak of the bloom, the exclusion of coccolithophores causes an increase in alkalinity of up to 4 μmol kg(sup −1) with a corresponding increase in DIC of up to 16 μmol kg(sup −1). During the peak of the bloom in summer, the net effect of the absence of the coccolithophores bloom is an increase in pCO2 of more than 20 μatm and a reduction of atmospheric CO2 uptake of more than 6 mmolm(sup −2) d(sup −1). On average, the impact of coccolithophores is an increase of air-sea CO2 flux of about 27 %. Considering the areal extent of the bloom from satellite images within the Irminger and Icelandic Basins, this reduction translates into an annual mean of nearly 1500 tonnes C yr(sup −1).

Earth Resources↗

NASA NTRS1987

Effects of fire on composition, biomass, and nutrients in oak scrub vegetation on John F. Kennedy Space Center, Florida

Four stands of oak scrub two, four, eight, and 25 years since fire were sampled with permanent 15 m line transects. Percent cover by species was determined. Plant samples were analyzed for a variety of substances. Transects were resurveyed in 1985 for vegetation parameters. Nutrient pools in biomass were calculated from biomass data and tissue nutrient concentrations. Soil nutrient pools were calculated from nutrient concentrations and bulk density. Species distribution and soil chemical properties were found to be closely related to water table depth. The following fire-related conclusions are reached: (1) major structural changes occur in scrub after fire in that shrub height is reduced and requires four to six years to exceed 1 m; (2) reduction in shrub height affects the suitability of scrub for the Florida scrub jay (3) live biomass increases with time since fire; (4) nutrient concentrations in live biomass do not change with time since fire; (5) species composition and richness are little changed after fire; and (6) imposition of a continued regime of burning on a three-year cycle may have adverse impacts not indicated by the recovery of scrub from a single fire.

Schmalzer, Paul A.↗

DOE OSTI2025

Estimating Switchgrass Biomass Yield and Lignocellulose Composition from UAV-Based Indices

Innovative methods for estimating commercial-scale switchgrass yields and feedstock quality are essential to optimize harvest logistics and biorefinery efficiency for sustainable aviation fuel production. This study utilized vegetation indices (VIs) derived from multispectral images to predict biomass yield and lignocellulose concentrations of advanced bioenergy-type switchgrass cultivars (“Liberty” and “Independence”) under two N rates (28 and 56 kg N ha –1 ). Field-scale plots were arranged in a randomized complete block design (RCBD) and replicated three times at Urbana, IL. Multispectral images captured during the 2021–2023 growing seasons were used to extract VIs. The results show that linear and exponential models outperformed partial least square and random forest models, with mid-August imagery providing the best predictions for biomass, cellulose, and hemicellulose. The green normalized difference vegetation index (GNDVI) was the best univariate predictor for biomass yield (R 2 = 0.86), while a multivariate combination of the GNDVI and normalized difference red-edge index (NDRE) enhanced prediction accuracy (R 2 = 0.88). Cellulose was best predicted using the NDRE (R 2 = 0.53), whereas hemicellulose prediction was most effective with a multivariate model combining the GNDVI, NDRE, NDVI, and green ratio vegetation index (GRVI) (R 2 = 0.44). These findings demonstrate the potential of UAV-based VIs for the in-season estimation of biomass yield and cellulose concentration.

09 BIOMASS FUELS↗