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

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At least 19 records

Feedstock Harvesting and Storage: Post-Harvest Management for Quality Preservation

Research on harvesting, collection, and storage has matured, and our understanding of feedstock supply challenges has led us to the point of our current goals. The goals of this project include using storage time to collect impactful data of critical feedstock properties in storage and to characterize the feedstock before delivery. This data will inform delivery scheduling of biomass and relevant compositional information to minimize variations in the material quality, which are critical to the preprocessing and conversion performance.

09 BIOMASS FUELS↗

Feedstock-Conversion Interface Consortium: Annual Review of Research – FY2020

The Feedstock-Conversion Interface Consortium (FCIC) published its Annual Review of Research FY2020 report, which presents an overview of the accomplishments of FCIC researchers for fiscal year 2020, covering both the low- and high-temperature conversion pathways and all three process areas (feedstock harvest and storage, preprocessing, and conversion).

09 BIOMASS FUELS↗

Effect of digestate and digestate supplemented with biochar on switchgrass growth and chemical composition

Digestate, a by-product of anaerobic digestion, can be an excellent source of nutrients for bioenergy crop production, while biochar, resulting from pyrolyzing biomass, can valorize the nutrients of digestate. The objective of this study was to evaluate the nutritional value of digestate and digestate + biochar for switchgrass production. The greenhouse experiment was conducted to determine the effects of a nitrogen (N) source including 0 N (control), urea (nutrient control), sewage sludge digestate, and sewage sludge digestate + corn stover biochar on switchgrass growth and feedstock composition. Nitrogen sources were observed to significantly increase plant weight at the 32-week harvest, with weight ranging from 94.2 to 125.2 g plant -1 , depending on the N source, compared to 70.7 g plant -1 from the negative control. Moreover, switchgrass treated with digestate + biochar showed higher plant weight than samples treated only with digestate. Nitrogen application of urea, digestate, and digestate + biochar had positive effects on plant height and total leaf area in the 32-week harvests and chlorophyll content in the 8-week harvests. Feedstock quality traits including hemicellulose, cellulose, and lignin content were not affected by N sources in either the 8 or 32-week harvests with the exception of ash concentration in the 32-week harvests. Our results indicate that digestate and digestate + biochar can be a potential substitute for chemical fertilizer, resulting in increased biomass yield.

09 BIOMASS FUELS↗

Effect of Feedstock Variability, Feedstock Blends, and Pretreatment Conditions on Sugar Yield and Production Costs

Mass production of sustainable biofuels replacing fossil fuels will significantly reduce global greenhouse gas emissions. However, biomass feedstock variability, availability, and affordability pose significant risks for the sustainable production of biofuels in biorefinery plants. To derisk the sustainable production of biofuels, this work investigates the sugar yields and production costs of four different feedstocks as well as their blends, using different pretreatment methods: deacetylation and dilute acid pretreatment (DDA) and deacetylation and mechanical refining pretreatment (DMR). We found that not only feedstock species variability, but also feedstock harvesting techniques have large impacts on both sugar yields and production costs. Single-pass harvested corn stover (SPCS) showed higher sugar yields and lower production costs than multipass harvested corn stover, followed by sorghum and switchgrass. The highest glucose yields of 91% and 95.3%, which corresponds to the lowest sugar production costs of $0.2286/lb. and $0.2490/lb., were observed for SPCS using DDA and DMR, respectively. The difference in sugar yields and production costs due to feedstock variability can be largely mitigated by increasing deacetylation severity, especially in DMR. Higher deacetylation severity resulted in decreased sugar production costs in the case of DMR in contrast to increased costs in the case of DDA. Blending switchgrass and sorghum into corn stover, which can significantly increase the feedstock availability and sustainability, resulted in sugar yields and production costs of roughly the weighted average of those derived from constituent individual feedstocks, respectively. Thus, blending feedstocks of different biomass species is a potential successful strategy for sustainable production of biofuels to replace fossil-derived fuels.

09 BIOMASS FUELS↗

Feedstock-Conversion Interface Consortium Annual Review of Research – FY 2021

Led by the U.S. Department of Energy’s Bioenergy Technologies Office, the Feedstock-Conversion Interface Consortium (FCIC) is a multi-lab collaboration that develops first-principles-based knowledge and tools to understand, quantify, and mitigate the effects of feedstock and process variability across the bioenergy value chain, from the field and forest through downstream conversion. The FCIC recently published its Annual Review of Research Fiscal Year (FY) 2021 report, which presents an overview of the research accomplishments of FCIC members in FY 2021, covering both the low- and high-temperature conversion pathways and all three process areas: Feedstock harvest and storage Preprocessing Conversion. The key research achievements of each task are presented, along with planned FY 2022 work that will build on the FY 2021 accomplishments.

09 BIOMASS FUELS↗

Stochastic Techno Economic Model

The Stochastic Techno-Economic Model or STEM is an analytical tool that estimates the logistics cost of different biomass feedstocks by incorporating uncertainty into the modeling framework. The scope of the model covers multiple stages of the biomass life cycle spanning feedstock harvest, collection, transportation and handling, preprocessing, and storage. The model determines the total logistics cost per dry metric ton ($/DM ton) for biomass and breaks down the costs for important cost categories including ownership related costs such as interest and depreciation, insurance, housing, and taxes as well as operating costs like repairs and maintenance, labor costs, and fuel and lube costs.

Burli, PralhadH↗

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↗

Life Cycle Assessment of Bioethanol Production: A Case Study from Poplar Biomass Growth in the U.S. Pacific Northwest

Biomass appears to be one of the most prominent renewable resources for biofuels such as bioethanol, mainly due to its better environmental performance compared with fossil fuels. This study addresses a comprehensive environmental performance of bioethanol production, employing empirical data from hybrid poplar grown in the U.S. The study considers 1 MJ as a functional unit and employs a cradle-to-grave approach, which entails the feedstock and harvesting production of poplar, transport to a biorefinery, bioconversion of the biomass process, and fuel use. On average, bioconversion is the main contributor to environmental degradation in all the categories evaluated (77%). The second main contributor is either the feedstock and harvesting production of poplar (17%) or fuel use (6%), depending on the environmental category. Thus, focusing on only one category may induce a misinterpretation of the environmental performance of bioethanol production. Finally, environmental credits in the global warming potential (GWP) category were obtained from the carbon sequestered in the biomass during the growing period and from avoided fossil fuel emissions due to electricity production from a renewable source. This means that the net GWP of the life cycle of bioethanol from poplar biomass is slightly negative (–1.05 × 10 –3 kg CO 2 -eq·MJ –1 ).

09 BIOMASS FUELS↗

Integrated Biomass Supply Analysis and Logistics Model (IBSAL) 2.0

The Integrated Biomass Supply Analysis and Logistics (IBSAL) 2.0 models a feedstock supply shed's harvest and transport process to estimate the cost of delivered feedstock. The model sets up a supply shed of fields, harvests the fields using a series of sequential harvest operations with different crew types, and transports the harvested feedstock to a storage facility or refinery. The model reports many metrics; the most important ones include the crew resources required for harvest and transport operations, equipment utilization, fuel usage, amount of dry mass harvested, the cost for each operation, and the expected time to complete the harvest with the provided resources. IBSAL 2.0 is a complete redesign around the ExtendSim database, and it is faster and easier to reapply the model to different feedstocks.

09 BIOMASS FUELS↗

Enabling Sustainable Landscape Design for Continual Improvement of Operating Bioenergy Supply Systems

This unique and highly effective project catalyzed collaboration among government, university, and private sector partners through a multi-state research and technology transfer project designed to support continuous improvement of bioenergy feedstock supply systems. Conceived and built upon the foundation created by prior DOE investments in the Billion Ton Study, Sun Grant Regional Project, and many other feedstock production, harvest, storage and transportation studies, this project addressed seven tasks with more than 29 subtasks. All goals were met with key accomplishments being: (1) on-farm establishment of potential perennial plant mixtures that could not only become sustainable feedstock sources but also enhance soil health, (2) a reduction in potential wind and water erosion by improving corn stover harvest techniques and incorporating cover crops into current row-crop production systems, (3) reduced potential for surface and groundwater contamination while also increasing potential biodiversity and sustainability of Midwestern USA landscapes, and (4) development of site-specific land management, data visualization, and sustainability assessment tools. Twenty-two Case Studies highlighting accomplishments and lessons learned through this public-private partnership investment are incorporated into this final report. On-farm and replicated field plot studies were used to provide the real-world data needed to verify baseline assumptions for extensive feedstock logistic modeling and greenhouse gas (GHG) assessments needed to develop sustainable bioenergy and bio-product industries at national and international scales.

09 BIOMASS FUELS↗

Harvest and nitrogen effects on bioenergy feedstock quality of grass-legume mixtures on Conservation Reserve Program grasslands

Perennial grass mixtures established on Conservation Reserve Program (CRP) lands can be an important source of feedstock for bioenergy production. This study aimed to evaluate management practices for optimizing the quality of bioenergy feedstock and stand persistence of grass-legume mixtures under diverse environments. A 5-year field study (2008–2012) was conducted to assess the effects of two harvest timings (at anthesis vs after complete senescence) and three nitrogen (N) rates (0, 56, 112 kg N ha -1 ) on biomass chemical compositions (i.e., cell wall components, ash, volatiles, total carbon, and N contents) and the feedstock energy potential, examined by the theoretical ethanol yield (TEY) and the total TEY (i.e., the product of biomass yield and TEY, L ha -1 ), of cool-season mixtures in Georgia and Missouri and a warm-season mixture in Kansas. The canonical correlation analysis (CCA) was used to investigate the effect of vegetative species transitions on feedstock quality. Although environmental variations (mainly precipitation) greatly influenced the management effect on chemical compositions, the delayed harvest after senescence generally improved feedstock quality. In particular, the overall cell wall concentrations and TEY of the warm-season mixtures increased by approximately 7%. Additional N supplies improved the total TEY of both mixtures by ~1.6–4.2 L ha -1 per 1.0 kg N ha -1 input but likely lowered the feedstock quality, particularly for the cool-season mixture. The cell wall concentrations of cool-season mixture reduced by approximately 3%–6%. The CCA results indicated that the increased legume compositions (under low N input) likely enhanced lignin but reduced ash concentrations. This field research demonstrated that with proper management, grass-legume mixtures on CRP lands can provide high-quality feedstock for bioenergy productions.

09 BIOMASS FUELS↗

Storage-Induced Collapse of Lignin Macromolecular Structure and Its Impacts on the Biorefinery

Lignin plays a vital role in the economics of biorefineries, serving as a source of process energy and a feedstock for sustainable fuels and chemical production. While understanding lignin’s chemical composition is crucial, emerging evidence suggests that a more comprehensive understanding of its macromolecular structure is critical to explaining its complex behavior in the biorefinery. This study investigated the partial collapse of the lignin network in corn stover feedstock after harvest and storage as a result of the microbial digestion of hemicellulose. Fluorescence microscopy was used to detect the collapse of lignin in terms of lignin’s inter-molecular interaction and the re-orientation of lignin’s chromophores, by the changes in lignin’s fluorescence lifetime, anisotropy, and the number of effective emitters. With minimal sample perturbation, our in-situ microscopic results revealed lignin's coil-globule transition phenomena, which was only previously predicted by molecular dynamics modeling extracted lignin in solvent. This collapse of lignin macromolecular structure was confirmed by results from NMR, IR, Raman, and powder X-ray diffraction. We also investigated the impact of this storage-induced collapse on the downstream biorefinery processes. Our study revealed that the two major approaches for lignin valorization in the lignin-first biorefinery model, namely monomer extraction and milled wood lignin extraction, were negatively impacted by the lignin collapse. As changes during storage are a source of feedstock variability, our study highlights the importance of understanding the effect of feedstock handling on biorefinery operations and economics.

09 BIOMASS FUELS↗

Forest residue harvest optimization: spanning the bridge between plant biology and biorefinery performance

Forestry residues have immense potential as alternative feedstocks to petroleum, yet their inherent complexity remains a major challenge to widespread use. Pairing the temporal rhythms of plant biology with biorefinery performance is critical to industrial-scale biorefinery development. Here, we provide the first report of a techno-economic analysis (TEA) and life cycle assessment (LCA) for a model integrated reductive catalytic fractionation (RCF)–molten salt hydrolysis process for forestry residues varying in tree part, species, and phenophase. All forestry residues resulted in net-negative greenhouse gas (GHG) emissions vs. comparable petroleum feedstocks, with GHG emissions potentially reduced >4.0× through composition-based feedstock selection (e.g., harvesting American beech bark in spring vs. summer). Moreover, American beech twigs/branchlets and bark in leafed and emergence phenophases, respectively, had 7.9× lower predicted phenolic minimum selling prices (MSPs) vs. other feedstocks and MSPs within the current global phenolic market range. Hemicellulose content and RCF yield emerged as key parameters impacting GHG emissions and biorefinery revenue, identifying hardwood twigs/branchlets in the leafed phenophase as optimal biofeedstocks. Biorefinery expenses were dominated by purchased equipment, raw materials, and utility costs, highlighting essential areas for future study. Notably, RCF reactor pressures drove 85–90% of equipment costs, but sensitivity analysis revealed that decreasing the pressure 20% could reduce the phenol MSP 4-fold. Structural carbohydrate dynamics were also investigated using a two-step acid hydrolysis method to resolve tissue- and species-level patterns in biomass composition throughout the year to enable harvest optimization based on TEA/LCA findings. Ultimately, elucidating the impact of biofeedstock dynamics on biorefinery performance enables harvest optimization, informed engineering design, and progress towards an expanded bioeconomy.

Shapiro, Alison J. [University of Delaware, Newark↗

Co-Harvest and Anaerobic Co-Storage of Corn Grain and Stover as Biomass Feedstocks

This research investigated the utility of co-harvesting and anaerobic co-storage of corn grain and stover to positively influence their physical and chemical characteristics as a biomass feedstock. Corn grain and stover were harvested in 2019 and 2020 with a self-propelled forage harvester. Stover yield, moisture content, and composition were altered by the harvest date, stubble height, and header configuration. Harvest date had the utility of varying the stover moisture content (p < 0.001) from 42.3% to 53.5% (w.b.) and 43.1% to 53.9% (w.b.) for the 2019 and 2020 harvest years, respectively. Stubble height was also utilized to vary stover moisture content. A negative linear relationship was established between stubble height and stover moisture content for the early (R2 = 0.76) and late harvest (R2 = 0.91) dates for both years. Stover yield also showed a negative linear relationship (R2 = 0.76) with stubble height over both years. Regardless of the stubble height, the row-crop header collected more stover (p < 0.001) than the ear-snapper header. In 2020, harvested stover ranged from 5.0 to 10.5 Mg ha-1, with ha-1 representing 41% to 85% of the total available stover. In both years, stover ash content was less than 64 g kg-1. Material stored in pilot-scale silos (19 L) was well conserved during anaerobic storage, with average DM losses of 4.8% and 3.4% in 2019 and 2020, respectively. Grain moisture content averaged 23.6% (w.b.) at harvest, and 31.0% (w.b.) after storage as moisture migrated from the moist stover to the drier grain. Harvesting whole-plant corn with a forage harvester had the unwanted effect of reducing the particle size of the grain fraction, which would complicate downstream utilization. However, reducing the harvester cutterhead speed increased the fraction of intact kernels from 47% to 85% by mass. The studied system was a viable alternative to conventional corn grain and stover systems for producing feedstocks for biochemical conversion.

09 BIOMASS FUELS↗

Soil organic matter and plant carbon allocated to nitrogen acquisition simulated by the FUN-BioCROP model

This data package contains the model input, results, and validation data from Juice et al (citation below). The FUN-BioCROP model (Fixation and Uptake of Nitrogen- Bioenergy Carbon, Rhizosphere, Organisms, and Protection) advances the field of bioenergy modeling by integrating new empirical paradigms of the role of belowground processes in shaping coupled carbon (C) and nitrogen (N) cycles. It was developed by modifying the FUN-CORPSE model (Fixation and Uptake of Nitrogen- Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment, Sulman et al. 2017 Ecology Letters) for use in bioenergy systems by including mechanistic tillage, organic matter addition, nitrogen fertilization, harvest, and feedstock-specific parameters, and to be driven by DayCent plant productivity and biomass data.

biofuel sustainability↗

Optimizing bioenergy biofuel harvest: a comparative analysis of stepwise and integrated methods for economic and environmental sustainability

Switchgrass is a promising bioenergy feedstock due to its high biomass yield potential, adaptability to marginal lands, and low carbon intensity for feedstock production. However, accurate cost estimation and assessment of greenhouse gas (GHG) emissions for the energy-intensive harvesting process are essential for evaluating the sustainability of bioenergy. This study provides a comparative analysis of two harvesting methods: the Stepwise Method, which separates operations into multiple stages, and the Integrated Method, which combines mowing and raking into a single pass. The analysis was conducted under four scenarios based on field sizes and biomass yields. Using three years of field-scale switchgrass harvest data from 125 sites, GHG emissions, energy consumption, and harvesting costs were quantified using the GREET model and techno-economic analysis. Additionally, regression analysis identified key climate and operational factors affecting fuel consumption. The Stepwise method was the most cost-effective for large fields with high biomass yield, achieving the lowest harvesting costs ($37.70 per ton). In contrast, the Integrated Method performed better in small fields and low-yield conditions, reducing GHG emissions by 9 % and energy use by 5 %. Regression analysis confirmed that a larger field size reduced fuel consumption, while higher biomass yield and longer operational time increased fuel use. Maximum temperature also contributed to a slight increase in fuel consumption. Furthermore, these results provide actionable insights for optimizing harvesting strategies based on field-specific conditions and operational goals, contributing to the economic and environmental sustainability of bioenergy production.

60 APPLIED LIFE SCIENCES↗

The nth-plant scenario for blended feedstock conversion and preprocessing nationwide: biorefineries and depots

The sustainability of the biofuel industry depends on the development of a mature conversion technology on a national level that can take advantage of the economies of scale: the nth-plant. Defining the future location and supply logistics of conversion plants is imperative to ultimately transform the nation’s renewable biomass resources into cost-competitive, high-performance feedstock for production of biofuels and bioproducts. Since the US has put restrictions on production levels of conventional biofuels from edible resources, the nation needs to plan for the widespread accessibility and development of the cellulosic biofuel scenario. Conventional feedstock supply systems will be unable to handle cellulosic biomass nationwide, making it essential to expand the industry with an advanced feedstock supply system incorporating a distributed network of preprocessing depots and conversion plants, or biorefineries. Current studies are mostly limited to designing supply systems for specific regions of the country. We developed a national database with potential locations for depots and biorefineries to meet the nation’s target demand of cellulosic biofuel. Blended feedstock with switchgrass and corn stover (harvested by either a two- or three-pass method) are considered in a Mixed Integer Linear Programming model to deliver on-spec biomass that considers both, a desired quantity and quality at the biorefinery. A total delivered feedstock cost that is less than $79.07/dt (2016$) is evaluated for years 2022, 2030, and 2040. In 2022, 124 depots and 59 biorefineries could be supplied with 42.8 million dt of corn stover and switchgrass. In 2030 and 2040, the total accessible biomass could increase to 215% and 393% respectively when compared to 2022. However, an $8/dry tons reduction in targeted delivery cost could reduce total accessible biomass by 67%. Kansas, Nebraska, South Dakota and Texas were identified as potential states with a strong biofuel economy given that they had six or more biorefineries located in all scenarios. In some scenarios, Colorado, Alabama, Georgia, Minnesota, Mississippi and South Carolina would greatly benefit from a depot network as these could only deliver to a biorefinery in a nearby state. To elaborate the impact of a nationwide consideration, the findings were compared with existing literature for different US regions. We also present results for biorefinery capacities that are double, triple, and quadruple in size.

09 BIOMASS FUELS↗