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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ground-Active Arthropod Diversity Under Energycane and Biomass Sorghum Production

Energycane and biomass sorghum are two of the most promising cellulosic energy crops in the southeastern US. Research on these two energy crops has focused mainly on biomass production, and there is a lack of knowledge on their ability to promote biodiversity and ecosystem services. This paper presents results from a comprehensive study on ground-active arthropod diversity in seven sites across five states in the southeastern US (Florida, Georgia, Louisiana, Mississippi, and Texas). Pitfall traps were deployed four times during each crop season for energycane, biomass sorghum, and a local reference conventional crop from 2020 to 2022. Arthropod abundance (individuals/(trap × day)) values were 4.9 ± 0.46, 3.7 ± 0.18, and 2.6 ± 0.16 (mean ± stderr) for conventional crops, biomass sorghum, and energycane, respectively, with a significant difference found only between conventional crops and energycane. Individuals were identified to arthropod orders, and Hill’s diversity indices were calculated based on the number of individuals in each arthropod order instead of the number of individuals in each arthropod species. Order-based arthropod richness values were 5.3, 5.2, and 4.8 for biomass sorghum, conventional crops, and energycane, with significant difference found only between biomass sorghum and energycane. There was no significant difference in the order-based Shannon diversity and Simpson diversity between the three crop types. The effective number of arthropod orders for the two energy crops decreased from 5.0 to 3.4 to 2.9 with increasing order of diversity from arthropod richness to Shannon diversity to Simpson diversity. The explained variability by environmental factors also decreased with increasing Hill’s order of diversity. The results from this study indicate no significant advantage in order-based arthropod diversity in growing biomass sorghum and energycane. This research fills a critical knowledge gap in understanding the impacts of cellulosic energy crop production on biodiversity and ecosystem services.

Yang, Yubin↗
DOE OSTI2025

The Co-Firing of Pine Biomass and Waste Coal in 100 and 600 MW Power Plants: A Sustainable Approach to Reduce GHG Emissions

Climate change is a global issue that has gained much attention recently. Co-firing biomass with coal/waste coal reduces the electricity sector’s GHG emissions sustainably. This study uses commercial software to model waste coal and biomass co-firing in 100 MW and 600 MW power plants. The objective is to assess the effects of fluid types (subcritical and supercritical), plant capacities (100 MW and 600 MW), boiler types (pulverized coal and circulating fluidized bed boilers), biomass and waste coal co-firing ratios (0:100, 20:80, 40:60, 60:40, 80:20, and 100:0), and carbon capture and storage efficiencies (0%, 90%, 95%, and 97%) on performance parameters such as net plant efficiency, heat rate, net plant CO2 and SO2, and particulate matter emissions. The feedstocks selected for this investigation include anthracite waste coal and loblolly pine biomass. As the biomass fraction increases from 0% to 100%, co-fired power plants net efficiency increases by 3–8%. Supercritical plants had a 6% higher net plant efficiency than the subcritical plants. The study found that the biomass’s high heating value decreased the fuel flow rate and reduced plant CO2 emissions by 10–16%. With 100% biomass power plant feed and 90% carbon capture and storage efficiency, CO2 emissions drop by 83% and SO2 and PM emissions drop to zero.

Bhoi, Prakashbhai R. (ORCID:0000000333104888)↗
DOE OSTI2024

Use of polyamines in the pretreatment of biomass

The present invention provides for a method to deconstruct a biomass: the method comprising: (a) introducing a solvent comprising a polyamine, or a mixture of polyamines, to a biomass to dissolve at least part of solid biomass in the solvent, wherein the polyamine is a Brønsted or Lewis base, and/or the polyamine is a hydrogen bond donor and/or acceptor; (b) optionally introducing an enzyme and/or a microbe to the solubilized biomass mixture such that the enzyme and/or microbe produces a sugar from the solubilized biomass mixture; (c) optionally separating the sugar from the solubilized biomass mixture; and (d) optionally separating the lignan from the solubilized biomass mixture.

Source record↗
DOE OSTI2025

Economic and environmental performance of biomass gasification for renewable natural gas production in the context of the U.S. natural gas supply

Bioenergy technologies offer potential for reducing greenhouse gas (GHG) emissions. One such promising technology is biomass gasification, which is the conversion of biomass into renewable natural gas (RNG) for use with a natural gas combined-cycle power generation system. However, the associated economic and emission effects need to be better understood to enable optimal decision-making and avoid missed opportunities for enhancing efficiency and increasing system circularity. This analysis explores opportunities to (1) decarbonize natural-gas-based systems and (2) leverage the extensive US natural gas infrastructure to mobilize biomass resources to achieve environmental and economic benefits. Here, in this analysis, the research team used a spatially explicit biomass logistics model (integrated with relevant biomass availability, technoeconomic analysis, and life cycle assessment information) to simulate economically optimal biomass allocation for RNG production and use for decarbonization in the United States. Results show that the United States has the potential to produce 9203 million GJ of RNG within the expected range of $\$$12–30/GJ. Further analyses tested the overall RNG production system's sensitivity to economic and emissions parameters of nine different processes. The sensitivity analysis results indicate that the median carbon abatement cost of RNG is most sensitive to changes in emissions associated with conversion processes and land use changes. These findings provide a deeper understanding of RNG's economic and emission potential for decision-making and guiding future research.

09 BIOMASS FUELS↗
DOE OSTI2025

Enhancing the flowability of woody biomass slurries in wet biorefineries

Feeding wet lignocellulosic biomass (e.g., softwood and hardwood) slurries into high-pressure, high-temperature reactors at an industrially relevant scale presents significant challenges, such as process equipment plugging. Here, in this study, we investigate the possibility of improving the flowability of biomass slurries in an industrial scale wet biorefinery by tuning the physical and chemical characteristics of the biomass particles. To understand the effects of the chemical characteristics of woody biomass on flowability, cellulose pulp particles are produced from pulp sheets via knife milling, pelletizing, and crumbling. These cellulose pulp particles are processed for acid hydrolysis dehydration (AHDH) at one –tonne-per day pilot scale. The levulinic acid yield (a product of cellulose AHDH) and the flowability of the biomass particles are compared using market pulp, 1 mm crumbled pine softwood, a blend of 2 mm hammer-milled pine softwood with 10 wt.% bark, and 2 mm hammer-milled hardwood material with 10 wt.% bark (to represent forest residues). The results indicate that the presence of hemicellulose and lignin influences the flowability of lignocellulosic feedstocks. Crumbled wood particles show poor flowability at the pilot scale, while the presence of fine materials (less than 0.7 mm) and bark improves the flowability of biomass slurries without affecting the organic acid yields (based on C6 carbohydrate content).

09 - BIOMASS FUELS↗
DOE OSTI2020

Optimization of harvest and logistics for multiple lignocellulosic biomass feedstocks in the northeastern United States

A mixed-integer linear programming model was developed to optimize the multiple biomass feedstock supply chains, including feedstock establishment, harvest, storage, transportation, and preprocessing. The model was applied for analyses of multiple biomass feedstocks at county level for 13 states in the northeastern United States. In the base case with a demand of 180,000 dry Mg/year of biomass, the delivered costs ranged from $\$67.90$ to $\$86.97$ per dry Mg with an average of $\$79.58$ /dry Mg. The biomass delivered costs by county were from $\$67.90$ to 150.81 per dry Mg across the northeastern U.S. Considered the entire study area, the delivered cost averaged $\$85.30$ /dry Mg for forest residues, $\$84.47$ /dry Mg for hybrid willow, $\$99.68$ for switchgrass and $\$97.87$ per dry Mg for Miscanthus. Seventy seven out of 387 counties could be able to deliver biomass at $84 per dry Mg or less a target set by US DOE by 2022. A sensitivity analysis was also conducted to evaluate the effects of feedstock availability, feedstock price, moisture content, procurement radius, and facility demand on the delivered cost. Lastly, our results showed that procurement radius, facility capacity, and forest residue availability were the most sensitive factors affecting the biomass delivered costs.

09 BIOMASS FUELS↗
DOE OSTI2020

Solid-State NMR Studies of Solvent-Mediated, Acid-Catalyzed Woody Biomass Pretreatment for Enzymatic Conversion of Residual Cellulose

Enzymes selectively hydrolyze the carbohydrate fractions of lignocellulosic biomass into corresponding sugars, but these processes are limited by low yields and slow catalytic turnovers. Under certain conditions, the rates and yields of enzymatic sugar production can be increased by pretreating biomass using solvents, heat, and dilute acid catalysts. However, the mechanistic details underlying this behavior are not fully elucidated, and designing effective pretreatment strategies remains an empirical challenge. Herein, using a combination of solid-state and high-resolution magic-angle-spinning NMR, infrared spectroscopy, and X-ray diffractometry, we show that the extent to which cellulase enzymes are able to hydrolyze solvent-pretreated biomass can be understood in terms of the ability of the solvent to break the chemical linkages between cellulose and noncellulosic materials in the cell wall. This finding is of general significance to enzymatic biomass conversion research, and implications for designing improved biomass conversion strategies are discussed. Furthermore, these findings demonstrate the utility of solid-state NMR as a tool to elucidate the key chemical and physical changes that occur during the liquid-phase conversion of real biomass.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Recent advances in biomass pretreatment using biphasic solvent systems

The complexity and recalcitrance of lignocellulosic biomass seriously hinder its subsequent conversion to liquid fuels. To achieve high-value utilization of lignocellulosic biomass, the physical–chemical barrier should be overcome through appropriate pretreatment techniques to improve the accessibility of cellulose for efficient enzymatic hydrolysis. With the rapid emergence of novel pretreatment solvents, biphasic solvent pretreatments represent a nascent and green pretreatment method that has shown outstanding advantages and broad application prospects in the biorefinery of lignocellulosic substrates due to its ability to provide economically viable biomass upgrading, the separation process for products in the solvent phase, and the reutilization of solvents. Herein, different types of biphasic solvents (e.g., 2-methyltetrahydrofuran, methyl isobutyl ketone, 1-butanol, phenoxyethanol, ionic liquids, and deep eutectic solvents) were reviewed systematically, including the fundamental designs of biphasic solvents for biomass pretreatment, their effect on the fractionation of individual biomass components (e.g., carbohydrate and lignin) and the enzymatic hydrolysis performance, and the coproduction of furan and hydroxymethylfurfural. Finally, the main pros and cons of these different biphasic solvent systems are summarized, and the future development direction is also proposed. Finally, this review can provide a reference for designing and selecting effective biphasic pretreatment methods for various types of lignocellulosic biomass.

09 BIOMASS FUELS↗
DOE OSTI2020

Deconstruction of biomass enabled by local demixing of cosolvents at cellulose and lignin surfaces

A particularly promising approach to deconstructing and fractionating lignocellulosic biomass to produce green renewable fuels and high-value chemicals pretreats the biomass with organic solvents in aqueous solution. Here, neutron scattering and molecular-dynamics simulations reveal the temperature-dependent morphological changes in poplar wood biomass during tetrahydrofuran (THF):water pretreatment and provide a mechanism by which the solvent components drive efficient biomass breakdown. Whereas lignin dissociates over a wide temperature range (>25 °C) cellulose disruption occurs only above 150 °C. Neutron scattering with contrast variation provides direct evidence for the formation of THF-rich nanoclusters (R g ∼ 0.5 nm) on the nonpolar cellulose surfaces and on hydrophobic lignin, and equivalent water-rich nanoclusters on polar cellulose surfaces. The disassembly of the amphiphilic biomass is thus enabled through the local demixing of highly functional cosolvents, THF and water, which preferentially solvate specific biomass surfaces so as to match the local solute polarity. A multiscale description of the efficiency of THF:water pretreatment is provided: matching polarity at the atomic scale prevents lignin aggregation and disrupts cellulose, leading to improvements in deconstruction at the macroscopic scale.

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 OSTI2020

<i>Finite Element Modeling of Biomass Hopper Flow</i>

The hopper is one of the widely used biomass handling devices that channels the bulk biomass from storage to the subsequent handling systems. Although Jenike's approach has been successfully used for hoppers handling grains and other agricultural produces for decades, designing a hopper, ensuring reliable biomass handling is found to be challenging. This study aims to address this engineering problem with alternative constitutive material models concerning the flow behavior of bulk solids. Finite element modeling is an approach that allows for implementing different material models. Underlying constitutive theories of different material models assist in investigating the mechanical behavior of a particulate system, including the flow characteristics of ground biomass. This study demonstrates hopper flow models of two types of biomass, i.e., ground corn stover and Douglas fir, with the Mohr-Coulomb model, which is based on Jenike's approach, modified Cam-Clay model, and Drucker-Prager/Cap model. The modeling results are compared with hopper flow experiments to highlights the advantages and shortfalls of each constitutive biomass flow model.

09 BIOMASS FUELS↗
DOE OSTI2024

Factorial experiment to identify two-way interactions between temperature, harvesting period, hydraulic retention time, and light intensity that influence the biomass productivity and phosphorus removal efficiency of a microalgae–bacteria biofilm

Rotating algae biofilm reactors (RABRs) can reduce energy requirements for wastewater reclamation but require further optimization for implementation at water resource recovery facilities (WRRF). Optimizing RABR operation is challenging because conditions at WRRF change frequently, and disregarding interaction terms related to these changes can produce incorrect conclusions about RABR behavior. This study evaluated the two-way interaction and main effects of four factors on the biomass productivity and phosphorus removal efficiency of a microalgae-bacteria biofilm grown in municipal anaerobic digester centrate, with factor levels and operating conditions selected to mimic a pilot RABR at a WRRF in Utah. Two-way interactions harvesting period*light intensity (LI), harvesting period*temperature, and LI*hydraulic retention time (HRT) had significant effects on biomass productivity: at high temperature and low LI, highest biomass productivity was achieved with a 14-day harvesting period, but at medium temperature and high LI, highest biomass productivity was achieved with a 7-day harvesting period. At high HRT, highest biomass productivity occurred at low LI, but at low HRT, highest biomass productivity occurred at high LI. Phosphorus removal was strongly influenced by LI and occurred most rapidly during the first 2 days HRT, which suggests precipitation contributed significantly to phosphorus removal. These observations provide insight for further RABR optimization.

09 BIOMASS FUELS↗
DOE OSTI2020

Algal Biomass Production via Open Pond Algae Farm Cultivation: 2019 State of Technology and Future Research

NREL’s algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL’s “combined algae processing” (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL R&D projects. This report focuses on front-end algal biomass production, documenting the pertinent algal biomass cultivation parameters that were input to the NREL open pond algae farm model and reports on key process sustainability indicators for the biomass production stage including annual biomass yields, facility power demand, and water consumption.

09 BIOMASS FUELS↗
DOE OSTI2021

Algal Biomass Conversion to Fuels via Combined Algae Processing (CAP): 2020 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office. It allows for the impact of research progress to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked towards out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research consortium (DISCOVR) efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL research and development projects. This report focuses on back-end conversion of algal biomass through the CAP pathway, highlighting the 2020 updates to minimum fuel selling price (MFSP). Notably, this analysis marks the first time that polyurethane (PU) is included as a value-added coproduct in the SOT case. Relative to prior 2019 benchmarks, the 2020 CAP SOT achieved further MFSP reductions of over $4/gallon gasoline equivalent, reflective of (a) the inclusion of PU co-production, (b) reduced SOT biomass production costs, and (c) higher pretreatment sugar yield data.

09 BIOMASS FUELS↗
DOE OSTI2022

Algal Biomass Production via Open Pond Algae Farm Cultivation: 2021 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office. It allows for the impact of research progress to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked towards out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL research and development projects. This report focuses on front-end algal biomass production, documenting the pertinent algal biomass cultivation parameters that were input to the NREL open pond algae farm model based on the latest DISCOVR cultivation performance data. Relative to the fiscal year (FY) 2020 SOT at $683/ton or $603/ton for ASU and FA evaporation scenarios, respectively (unlined pond basis), the FY 2021 SOT represents a slight increase in MBSP of 1%-2%. This is primarily attributed to a slight 4% reduction in annual cultivation productivity achieved at the AzCATI site (supported by the efforts under the DISCOVR consortium noted above) observed during FY 2021 cultivation campaigns.

09 BIOMASS FUELS↗
DOE OSTI2022

Regional Feedstock Partnership Biomass Quality Assessment Final Report

The United States (U.S.) Department of Energy (DOE) developed the Billion-Ton Vision to enable production of one-billion tons of sustainable, reliable biomass for the bioenergy industry by 2030 (Perlack et al., 2005). The Sun Grant Regional Feedstock Partnership (RFP) was organized to fill information gaps and validate biomass yield assumptions related to the Billion-Ton Study (Owens, 2018; Owens, Karlen, and Lacey, 2016). Along with the more than 130 scientific publications generated from these studies, yield and sustainability data from the RFP field trials not only validated the Billion-Ton estimates, but were critical in developing both the U.S. Billion-Ton Update report in 2011 and the 2016 Billion-Ton Report (DOE, 2011; 2016). The intention of this biomass quality assessment report is to build on these initial successes from the RFP field trials by focusing on variability in biomass quality data necessary to evaluate conversion performance. This report contains a summary of chemical quality results from samples collected as part of the RFP field trials. This report focuses on assessment of the impact of experimental agronomic designs on biomass properties followed by analyses of the impact of environmental and production variables on biomass properties. Datasets include species and other genetic variables, fertilizer treatments, harvest information, and yield, as well as other publicly available data such as precipitation, temperature, soil properties, and drought. The key outcomes from this chemical quality focused assessment have included: • Complete evaluation of the impacts of agronomic designs, genetics, and environmental conditions on chemical properties for Miscanthus, switchgrass, sorghum, energycane, mixed perennial grasses, and shrub willow short-rotation feedstocks • Over 30 peer review publications and technical reports focused on variability in quality data • Development of spatial and temporal environmental quality prediction maps for Miscanthus and switchgrass feedstocks allowing for comprehensive evaluation of variability in feedstock chemical quality across U.S. regions and over multiple harvest years

09 BIOMASS FUELS↗
DOE OSTI2022

Algal Biomass Conversion to Fuels via Combined Algae Processing (CAP) (2021 State of Technology and Future Research)

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office. It allows for the impact of research progress to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked towards out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research consortium (DISCOVR) efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL research and development projects. This report focuses on back-end conversion of algal biomass through the CAP pathway, highlighting the 2021 updates to minimum fuel selling price (MFSP). This update maintains an important recent inclusion of polyurethane (PU) previously incorporated in the 2020 SOT as a value-added coproduct. Relative to the 2020 SOT case, this indicates a minimal increase of $0.10-$0.14/GGE (roughly 2%) for both the acids and BDO pathways, attributed to minimal increases in upstream algal biomass costs from slightly lower demonstrated cultivation productivities in the 2021 SOT.

09 BIOMASS FUELS↗
DOE OSTI2024

Precision Plant Biomass Characterization in Agriculture: Harnessing Machine Learning and Hyperspectral Imaging [Slides]

Efficient Biomass Separation Object detection of anatomical parts (Cob, Stalk, Husk) in IR images enables precise separation, improving preprocessing (e.g., drying, grinding) for biofuel production. Detailed Biomass Characterization with Hyperspectral Data Hyperspectral imaging captures spectral signatures of biomass, allowing for the identification of specific traits like moisture content, lignin levels, and nutrient composition, leading to optimized treatments for each biomass part. Enhanced Feedstock Quality By leveraging hyperspectral data, feedstock can be processed based on its chemical composition, improving conversion efficiency and biofuel yield. Automation for Large-Scale Operations Automated object detection and hyperspectral data analysis reduce manual labor, ensuring accurate sorting and faster processing, making large-scale biofuel production more efficient. Maximized Biomass Utilization Accurate identification of biomass properties minimizes waste and ensures that each part is processed according to its highest biofuel potential.

09 BIOMASS FUELS↗