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At least 253 records · Page 14

SPERLU Selective Process for Efficient Removal of Lignin and Upgrading (Final Technical Report)

To meet the growing demand for bio-based chemicals and improve the profitability and efficiency of the emerging biorefinery industry, lignin is an abundant and attractive feedstock. Spero Renewables has developed a proprietary and patent-pending technology, the Selective Process for Efficient Removal of Lignin and Upgrading (SPERLU). The technology is a catalytic deconstruction and upgrading of lignin in lignocellulosic biomass or commercially available technical lignin to produce multi-functional phenol (MFP) products. The SPERLU process has been demonstrated and vetted on a lab scale to convert commercially available technical lignin to MFPs in yields of 60-90% (based on lignin). The MFP products can be separated and further upgraded through catalytic or biological means. Spero performed a detailed kinetic study of the SPERLU process and used the resulting kinetic data to design and construct a mini-pilot-scale reactor for routine production of hundreds of grams of MFP products. Spero’s lignin-based MFPs have been demonstrated for use as a drop-in replacement for bisphenol A (BPA) in the synthesis of thermoset polymers. Spero’s lignin-based thermoset polymers exhibit excellent mechanical properties and can be used in many applications. Additionally, a collaboration with the National Renewable Energy Lab (NREL) was used to evaluate the feasibility of upgrading SPERLU products through biological means into valuable chemicals. A comprehensive technoeconomic analysis (TEA) and Life-cycle analysis (LCA) have been completed and support the case for commercialization of the SPERLU technology. Through this project Spero has significantly de-risked the SPERLU technology and is actively planning larger scale pilot projects.

09 BIOMASS FUELS↗

Satellites May Underestimate Rice Residue and Associated Burning Emissions in Vietnam

In this study, we estimate rice residue, associated burning emissions, and compare results with existing emissions inventories employing a bottom-up approach. We first estimated field-level post-harvest rice residues, including separate fuel-loading factors for rice straw and rice stubble. Results suggested fuel-loading factors of 0.27 kg/sq m (+/-0.033), 0.61 kg/sq m (+/-0.076), and 0.88 kg/sq m (+/-0.083) for rice straw, stubble, and total post-harvest biomass, respectively. Using these factors, we quantified potential emissions from rice residue burning and compared our estimates with other studies. Our results suggest total rice residue burning emissions as 2.24 Gg PM2.5, 36.54 Gg CO and 567.79 Gg CO2 for Hanoi Province, which are significantly higher than earlier studies. We attribute our higher emission estimates to improved fuel-loading factors; moreover, we infer that some earlier studies relying on residue-to-product ratios could be underestimating rice residue emissions by more than a factor of 2.3 for Hanoi, Vietnam. Using the rice planted area data from the Vietnamese government, and combining our fuel-loading factors, we also estimated rice residue PM2.5 emissions for the entirety of Vietnam and compared these estimates with an existing all-sources emissions inventory, and the Global Fire Emissions Database (GFED). Results suggest 75.98 Gg of PM2.5 released from rice residue burning accounting for 12.8% of total emissions for Vietnam. The GFED database suggests 42.56 Gg PM2.5 from biomass burning with 5.62 Gg attributed to agricultural waste burning indicating satellite-based methods may be significantly underestimating emissions. Our results not only provide improved residue and emission estimates, but also highlight the need for emissions mitigation from rice residue burning.

Air pollution↗

Rational design of photosynthetic reaction center protein maquettes

New technologies for efficient solar-to-fuel energy conversion will help facilitate a global shift from dependence on fossil fuels to renewable energy. Nature uses photosynthetic reaction centers to convert photon energy into a cascade of electron-transfer reactions that eventually produce chemical fuel. The design of new reaction centers de novo deepens our understanding of photosynthetic charge separation and may one day allow production of biofuels with higher thermodynamic efficiency than natural photosystems. Recently, we described the multi-step electron-transfer activity of a designed reaction center maquette protein (the RC maquette), which can assemble metal ions, tyrosine, a Zn tetrapyrrole, and heme into an electron-transport chain. Here, we detail our modular strategy for rational protein design and show that the intended RC maquette design agrees with crystal structures in various states of assembly. A flexible, dynamic apo-state collapses by design into a more ordered holo-state upon cofactor binding. Crystal structures illustrate the structural transitions upon binding of different cofactors. Spectroscopic assays demonstrate that the RC maquette binds various electron donors, pigments, and electron acceptors with high affinity. We close with a critique of the present RC maquette design and use electron-tunneling theory to envision a path toward a designed RC with a substantially higher thermodynamic efficiency than natural photosystems.

09 BIOMASS FUELS↗

Land‐based climate solutions for the United States

Abstract Meeting end‐of‐century global warming targets requires aggressive action on multiple fronts. Recent reports note the futility of addressing mitigation goals without fully engaging the agricultural sector, yet no available assessments combine both nature‐based solutions (reforestation, grassland and wetland protection, and agricultural practice change) and cellulosic bioenergy for a single geographic region. Collectively, these solutions might offer a suite of climate, biodiversity, and other benefits greater than either alone. Nature‐based solutions are largely constrained by the duration of carbon accrual in soils and forest biomass; each of these carbon pools will eventually saturate. Bioenergy solutions can last indefinitely but carry significant environmental risk if carelessly deployed. We detail a simplified scenario for the United States that illustrates the benefits of combining approaches. We assign a portion of non‐forested former cropland to bioenergy sufficient to meet projected mid‐century transportation needs, with the remainder assigned to nature‐based solutions such as reforestation. Bottom‐up mitigation potentials for the aggregate contributions of crop, grazing, forest, and bioenergy lands are assessed by including in a Monte Carlo model conservative ranges for cost‐effective local mitigation capacities, together with ranges for (a) areal extents that avoid double counting and include realistic adoption rates and (b) the projected duration of different carbon sinks. The projected duration illustrates the net effect of eventually saturating soil carbon pools in the case of most strategies, and additionally saturating biomass carbon pools in the case of forest management. Results show a conservative end‐of‐century mitigation capacity of 110 (57–178) Gt CO 2 e for the U.S., ~50% higher than existing estimates that prioritize nature‐based or bioenergy solutions separately. Further research is needed to shrink uncertainties, but there is sufficient confidence in the general magnitude and direction of a combined approach to plan for deployment now.

54 ENVIRONMENTAL SCIENCES↗

Connecting Indonesian Fires and Drought With the Type of El Niño and Phase of the Indian Ocean Dipole During 1979-2016

This study advances the previous understanding of the role of climate variability on Indonesian fire activity, by considering (i) the presence of different types of El Niño and (ii) the interaction between El Niño and the Indian Ocean Dipole (IOD). We classify 12 El Niño events during 1979-2016 into Eastern Pacific (EP) and Central Pacific (CP) types (four and eight El Niño events, respectively) and analyze observational data of sea surface temperature, precipitation, drought code, biomass burning carbon emission, visibility, and aerosol optical depth accordingly. We find that more intense and prolonged Indonesian drought and fires occur in the EP type, during which the emitted carbon amounts almost double those in the CP type. By further separating the CP type El Niño according to the phase of the IOD, that is, positive and negative, we show that fire seasons with less burning intensity and shorter duration are predominantly associated with weakly positive or even negative phase of the IOD phenomena. Moreover, fire intensity exhibits geographic diversity: fires are always more intensive in southern Kalimantan than in southern Sumatra in all El Niño events, although it is less dry in the former region. The outcome of this study can be applied to drought early warning, fire management, and air quality forecast in Indonesia and adjacent areas by identifying the type of El Niño and the phase of the IOD in advance.

IOD phenomena↗

Chloroform Fumigation Extraction for Microbial Biomass and Dissolved Organic Carbon from SPRUCE, Marcell Experimental Forest, Minnesota, 2021, 2022, and 2024

This data set provides the results for chloroform fumigation extraction (CFE) of peat samples collected from ambient and experimental plots in the Spruce and Peatland Responses Under Environmental Change (SPRUCE) Experiment site in June and August of 2021, June of 2022, and June, August, and October of 2024. The SPRUCE Experiment site is in the Marcell Experimental Forest in northern Minnesota, USA. The data set includes values for microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), dissolved organic carbon (DOC), dissolved nitrogen (DN), moisture content (MC, available for 2021 and 2022 only) and gravimetric water content (GWC) at 11 depth increments of two-meter peat cores taken from 12 sampling sites at SPRUCE (10 temperature treatment enclosures, 2 ambient temperature treatment enclosures). The sample analysis followed standard methods. The samples were analyzed using a Shimadzu Total Organic Carbon/Nitrogen (TOC/N) analyzer (TOC-V and TOC-L; 2021-2022) or an Elementar vario TOC Cube (2024), liquid catalytic oxidation combustion analyzers for total carbon and nitrogen analysis. This dataset contains two data files in comma separate (.csv) format. Additional metadata are provided: two data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

dissolved nitrogen↗

Improving CLM5.0 Biomass and Carbon Exchange Across the Western United States Using a Data Assimilation System

The Western United States is dominated by natural lands that play a critical role for carbon balance, water quality, and timber reserves. This region is also particularly vulnerable to forest mortality from drought, insect attack, and wildfires, thus requiring constant monitoring to assess ecosystem health. Carbon monitoring techniques are challenged by the complex mountainous terrain, thus there is an opportunity for data assimilation systems that combine land surface models and satellite-derived observations to provide improved carbon monitoring. Here, we use the Data Assimilation Research Testbed to adjust the Community Land Model (CLM5.0) with remotely sensed observations of leaf area and above-ground biomass. The adjusted simulation significantly reduced the above-ground biomass and leaf area, leading to a reduction in both photosynthesis and respiration fluxes. The reduction in the carbon fluxes mostly offset, thus both the adjusted and free simulation projected a weak carbon sink to the land. This result differed from a separate observation-constrained model (FLUXCOM) that projected strong carbon uptake to the land. Simulation diagnostics suggested water limitation had an important influence upon the magnitude and spatial pattern of carbon uptake through photosynthesis. We recommend that additional observations important for water cycling (e.g., snow water equivalent, land surface temperature) be included to improve the veracity of the spatial pattern in carbon uptake. Furthermore, the assimilation system should be enhanced to maximize the number of the simulated state variables that are adjusted, especially those related to the recommended observed quantities including water cycling and soil carbon.

54 ENVIRONMENTAL SCIENCES↗

Integrated Active Fire Retrievals and Biomass Burning Emissions Using Complementary Near-Coincident Ground, Airborne and Spaceborne Sensor Data

Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing high quality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (less than 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5 difference between AquaMODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg per MJ, total energy release of 14.5 x 10(exp 6) MJ, and total fuel consumption of 3.8 x 10(exp 6) kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15 difference for various species

airborne scanner↗

Bio-Based Acetonitrile Production

The purpose of this CRADA is to produce at minimum 100 g of specified (99.8 wt%) acetonitrile from the nitrilation reaction using commercially available biologically derived acetic acid. This CRADA will also investigate the separation of pullulan from fermentation broth.

09 BIOMASS FUELS↗

Effect of Carboxylic Acids on Corrosion of Type 410 Stainless Steel in Pyrolysis Bio-Oil

Biomass-derived oils are renewable fuel sources and commodity products and are proposed to partially or entirely replace fossil fuels in sectors generally considered difficult to decarbonize such as aviation and maritime propulsion. Bio-oils contain a range of organic compounds with varying functional groups which can lead to polarity-driven phase separation and corrosion of containment materials during processing and storage. Polar compounds, such as organic acids and other oxygenates, are abundant in bio-oils and are considered corrosive to structural alloys, particularly to those with a low-Cr content. To study the corrosion effects of small carboxylic acids present in pyrolysis bio-oils, type 410 stainless steel (SS410) specimens were exposed in bio-oils with varying formic, acetic, propionic and hexanoic acid contents at 50 °C during 48 h exposures. The specific mass change data show a linear increase in mass loss with increasing formic acid concentration. Interestingly, a mild corrosion inhibition effect on the corrosion of SS410 specimens was observed with the addition of acetic, propionic and hexanoic acids in the bio-oil.

09 BIOMASS FUELS↗

Mapping of taiga forest units using AIRSAR data and/or optical data, and retrieval of forest parameters

A maximum a posteriori Bayesian classifier for multifrequency polarimetric SAR data is used to perform a supervised classification of forest types in the floodplains of Alaska. The image classes include white spruce, balsam poplar, black spruce, alder, non-forests, and open water. The authors investigate the effect on classification accuracy of changing environmental conditions, and of frequency and polarization of the signal. The highest classification accuracy (86 percent correctly classified forest pixels, and 91 percent overall) is obtained combining L- and C-band frequencies fully polarimetric on a date where the forest is just recovering from flooding. The forest map compares favorably with a vegetation map assembled from digitized aerial photos which took five years for completion, and address the state of the forest in 1978, ignoring subsequent fires, changes in the course of the river, clear-cutting of trees, and tree growth. HV-polarization is the most useful polarization at L- and C-band for classification. C-band VV (ERS-1 mode) and L-band HH (J-ERS-1 mode) alone or combined yield unsatisfactory classification accuracies. Additional data acquired in the winter season during thawed and frozen days yield classification accuracies respectively 20 percent and 30 percent lower due to a greater confusion between conifers and deciduous trees. Data acquired at the peak of flooding in May 1991 also yield classification accuracies 10 percent lower because of dominant trunk-ground interactions which mask out finer differences in radar backscatter between tree species. Combination of several of these dates does not improve classification accuracy. For comparison, panchromatic optical data acquired by SPOT in the summer season of 1991 are used to classify the same area. The classification accuracy (78 percent for the forest types and 90 percent if open water is included) is lower than that obtained with AIRSAR although conifers and deciduous trees are better separated due to the presence of leaves on the deciduous trees. Optical data do not separate black spruce and white spruce as well as SAR data, cannot separate alder from balsam poplar, and are of course limited by the frequent cloud cover in the polar regions. Yet, combining SPOT and AIRSAR offers better chances to identify vegetation types independent of ground truth information using a combination of NDVI indexes from SPOT, biomass numbers from AIRSAR, and a segmentation map from either one.

Rignot, Eric↗

Anaerobic Dynamic Membrane Bioreactor Development to Facilitate Organic Waste Conversion to Medium-Chain Carboxylic Acids and Their Downstream Recovery

Platform chemicals such as medium-chain carboxylic acids (MCCAs) can be produced from organic waste streams via chain elongation in anaerobic mixed-culture bioreactors. A product recovery system is needed to collect MCCAs from the bioreactor effluent. Membrane-based liquid–liquid extraction, the most commonly used product recovery approach, requires suspended solids removal from the bioreactor effluent to avoid membrane fouling. An anaerobic dynamic membrane bioreactor (AnDMBR) was developed to evaluate MCCA production from brewery and prefermented food waste and to produce a permeate with low suspended solids to facilitate downstream product recovery. The AnDMBR employed an inexpensive stainless-steel mesh as the support material for the development of a biofilm or dynamic membrane, which was responsible for solids–liquid separation. The AnDMBR produced a permeate quality with an average total suspended solids (TSS) concentration of 0.12 g L –1 , while the average bioreactor TSS concentration was two orders of magnitude higher (21.6 g L –1 ). A maximum solids removal efficiency of ≥99% was achieved and good permeate quality was sustained for over 200 days without fouling control or cleaning the support material. In addition to solids–liquid separation, the dynamic membrane was responsible for a substantial fraction of the biological activity of the AnDMBR. The relative activity of Clostridiales, as determined by 16S rRNA sequencing, correlated with MCCA production and was higher in the dynamic membrane (20.0 ± 4.9%) than in the suspended biomass (5.2 ± 2.7%) in the bioreactor. This observation was consistent with MCCA production data as the permeate MCCA concentrations were significantly (p = 8.2 × 10 –5 ) higher than that in the bioreactor, suggesting that the dynamic membrane biofilm contributed to chain elongation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bioleaching to produce clean loblolly pine for thermochemical conversion

Lignocellulosic biomass contains inorganic elements that could induce slagging, ash fouling, and emission of both corrosive and harmful gases during thermochemical conversion. Water leaching pretreatment can remove most of the water-soluble elements, while it has limited industrial applicability due to its ineffectiveness in removing water-insoluble elements. Bioleaching is an alternative pretreatment method which has not been fully studied. In this work, bioleaching by Aspergillus niger strains NRRL 2001, NRRL 3122, and NRRL 567 was conducted to pretreat loblolly pine biomass with added water. Further, the removal of inorganic elements (K, Ca, Mg, and S) by bioleaching with A. niger NRRL 2001 was compared with chemical leaching with citric acid, HCl, and NaOH. It was shown that the pH reduction during bioleaching greatly improved K and Mg leaching to the point comparable to acid leaching, whereas Ca was precipitated by oxalic acid produced by the fungus. Bioleaching was also conducted in manually separated needles and chips components of loblolly pine. Glucose was added at different levels to assist bioleaching. At higher glucose levels, gluconic acid and citric acid were produced during bioleaching, leading to the increase of K, Ca, and Mg removal rates by more than 35%, 180%, and 390%, respectively, from the feedstock as compared with water leaching. Overall, bioleaching greatly improved removal of K, Ca, Mg, but not S from loblolly pine feedstocks as compared with water leaching.

09 BIOMASS FUELS↗

Q4 Milestone Report - Bioenergy Technologies Office

Objective: The objective of this task is to identify the costs of sorting municipal solid wastes (MSW) into different product streams that would be suitable for inclusion in potential low-cost feedstock blends. Expected Outcome: Progress Milestone – Complete a MSW sorting process model that includes unit operations of shredding, screening, sieving, air classification, magnetic separation and eddy current separation in conjunction with a MSW sorting equipment supplier. This model will be scalable such that it can be utilized in both large urban areas and rural areas.

09 BIOMASS FUELS↗

Discerning Influences from Enthalpy and Entropy at Aqueous Interfaces Involved in Biomass Conversions in Porous Catalysts

Project Summary: The goal in this proposal is to learn how solvent influences the enthalpies and entropies of catalytic species in zeolite pores. Specifically, the physical, chemical, and structural features of solvent, catalytic species, and zeolite pores that determine enthalpies and entropies of solvation in solution phase biomass conversions will be interrogated using multiscale simulations and machine learning. Multiscale simulations are based off of existing strategies and employ quantum mechanics and classical molecular dynamics, providing an excellent balance between chemical accuracy and computational expense. They are capable of calculating enthalpies and entropies of solvation separately and have been validated in prior work to achieve high accuracy compared to their parent methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spectral Range Within Global aCDOM(440) Algorithms for Oceanic, Coastal, and Inland Waters with Application to Airborne Measurements

The optically active component of dissolved organic material in aquatic ecosystems, or colored dissolved organic matter (CDOM), is represented by the coefficient of absorption due to the dissolved aquatic constituents at 440 nm, aCDOM(440). Remote sensing of aCDOM(440) enables characterization of ecosystem processes and aids in retrieval of chlorophyll a, a proxy for phytoplankton biomass. Spectrally adjacent band-ratio domains, e.g., blue to green, have previously been applied for remote sensing of aCDOM(440) in coastal and oceanic waters with similar results compared to more complex semi-analytical algorithms. Estimation of aCDOM(440) from ratios of the most spectrally separated ocean color wavebands (end members), e.g., ultraviolet (UV) to near-infrared (NIR), termed end-member analysis (EMA), has previously been shown to increase the accuracy of global aCDOM(440) retrievals from in-water observations of diffuse attenuation and to enable a unified algorithmic perspective without requiring regional adjustment of internal bio-optical parameters. EMA of above-water observations is evaluated herein, with a focus on coastal and inland waters in which increasing optical complexity and likelihood of bottom reflectance challenge the oceanic algorithms developed for deep and optically simple (case-1) waters. Analysis herein of three independent, in situ, bio-optical datasets indicates significant correlation between aCDOM(440) and end-member band ratios (next-generation 320 and 780 nm or legacy 412 and 670 nm ratios) with a coefficient of determination, R2, of 0.87 (log-scale) or higher based on a dataset spanning the dynamic range of global, conservative water bodies. For applicable wavelengths, EMA algorithms are shown to agree with case-1 relationships and to produce consistent log-scale uncertainties across more than three orders of magnitude in aCDOM(440) values (0.001–2.305 m􀀀1). EMA using UV and NIR wavelengths (320 and 780 nm) is applied to low-altitude airborne observations and satisfies 25% uncertainty based on unbiased percent differences (UPDs) within each of three dissimilar match-up sites ranging in aCDOM(440) from 0.02–0.57 m􀀀1. Results demonstrate that EMA is a useful and robust approach for the remote sensing of aCDOM(440) in coastal and inland waters, which are generally shallower, contain more optically complex environments, and span a greater range in aCDOM(440) than oceanic waters.

CDOM↗

Develop Recovery Systems for Separations of Salts from Process Streams for use in Advanced Life Support System

The main objectives of this project were the development of a four-compartment electrolytic cell using high selective membranes to remove nitrate from crop residue leachate and convert it to nitric acid, and the development of an six compartment electrodialysis cell to remove selectively sodium from urine wastes. The recovery of both plant inedible biomass and human wastes nutrients to sustain a biomass production system are important aspects in the development of a controlled ecological life support system (CELSS) to provide the basic human needs required for life support during long term space missions. A four-compartment electrolytic cell has been proposed to remove selectively nitrate from crop residue and to convert it to nitric acid, which is actually used in the NASA-KSC Controlled Ecological Life Support System to control the pH of the aerobic bioreactors and biomass production chamber. Human activities in a closed system require large amount of air, water and minerals to sustain life and also generate wastes. Before using human wastes as nutrients, these must be treated to reduce organic content and to remove some minerals which have adverse effects on plant growth. Of all the minerals present in human urine, sodium chloride (NACl) is the only one that can not be used as nutrient for most plants. Human activities also requires sodium chloride as part of the diet. Therefore, technology to remove and recover sodium chloride from wastes is highly desirable. A six-compartment electrodialysis cell using high selective membranes has been proposed to remove and recover NaCl from human urine.

Colon, Guillermo↗