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At least 361 records · Page 20

Using Life Cycle Assessment to Inform CBI Research Priorities

Life cycle assessment (LCA) is used within the Center for Bioenergy Innovation (CBI) to provide information about how feedstock agricultural practices, supply chain logistics, biorefinery operating parameters, and the slate of biofuels and products contribute to environmental impacts, and how CBI's research priorities can result in less impactful biofuel supply chains. This poster provides an overview of the LCA methodology used within CBI and focuses on data needs in general and from other CBI teams. Assumptions and simplifications within biofuel LCA studies are reviewed, including options for modeling multi-functional processes. Calculation details for life cycle environmental impacts used within CBI - global warming potential, cumulative energy demand, and the Available Water Remaining indicator - are presented, along with a discussion of carbon intensity as an alternative metric for evaluating sustainable aviation fuel and other biofuels. The process of interpreting impact results to guide research priorities is discussed, with examples drawn from CBI's upcoming manuscript on switchgrass yield and cell wall composition.

bioenergy↗

Biomass formation and sugar release efficiency of Populus modified by altered expression of a NAC transcription factor

Woody biomass is an important feedstock for biofuel production. Manipulation of wood properties that enable efficient conversion of biomass to biofuel reduces cost of biofuel production. Wood cell wall composition is regulated at several levels that involve expression of transcription factors such as wood-/secondary cell wall-associated NAC domains (WND or SND). In Arabidopsis thaliana, SND1 regulates cell wall composition through activation of its down-stream targets such as MYBs. The functional aspects of SND1 homologs in the woody Populus have been studied through transgenic manipulation. In this study, we investigated the role of PdWND1B, Populus SND1 sequence ortholog, in wood formation using transgenic manipulation through over-expression or silencing under the control of a vascular-specific 4-coumarate-CoA ligase (4CL) promoter. As compared with control plants, PdWND1B-RNAi plants were shorter in height, with significantly reduced stem diameter and dry biomass, whereas there were no significant differences in growth and productivity of PdWND1B over-expression plants. Conversely, PdWND1B over-expression lines showed a significant reduction in cellulose and increase in lignin content, whereas there was no significant impact on lignin content of downregulated lines. Stem carbohydrate composition analysis revealed a decrease in glucose, mannose, arabinose, and galactose, but an increase in xylose in the over-expression lines. Transcriptome analysis revealed upregulation of several downstream transcription factors and secondary cell wall related structural genes in the PdWND1B over-expression lines, partly explaining the observed phenotypic changes in cell wall chemistry. Relative to the control, glucose release efficiency and ethanol production from stem biomass was significantly reduced in over-expression lines. Our results show that PdWND1B is an important factor determining biomass productivity, cell wall chemistry and its conversion to biofuels in Populus.

09 BIOMASS FUELS↗

Biomass carbon removal can help sustainable aviation fuels achieve on-time arrival

Biofuels, including sustainable aviation and marine fuels, and biomass carbon removal and storage (BiCRS) are often viewed as potentially competing pathways for advancing climate and energy goals. Their comparative economic, environmental, and temporal advantages remain debated. Rather than identifying a “best-use” for biomass, we show that the relative economic advantages of BiCRS versus biofuels exist along a continuum shaped by energy- and decarbonization-focused market conditions. These pathways need not be adversarial: BiCRS can enable, rather than displace, future biofuel deployment. While the lignocellulosic biofuel sector continues to face barriers associated with underdeveloped supply chains and technologies that have not yet been commercialized at scale, emerging BiCRS approaches are comparatively feedstock-flexible, rapidly deployable, and responsive to carbon removal markets. Early BiCRS deployment can help establish reliable biomass supply chains, reducing investment risk for future lignocellulosic biorefineries. By easing initial supply chain constraints, BiCRS can serve as a practical stepping stone toward meeting both near-term carbon removal needs and long-term sustainable fuel objectives under uncertain future market and policy conditions.

bioenvironmental engineering↗

Towards the sustainable conversion of corn stover into bioenergy and bioproducts through biochemical route: Technical, economic and strategic perspectives

Corn stover (CS) is one of the most abundant agricultural wastes and is ubiquitous around the world that is left over after grain harvest and accounts for 47–50% dry mass of the total grain yield. The global CS yield is 1661.25 million tons/year, which is 27.2% of the total agricultural waste. CS consists of about 34.5% stems, 32.3% leaves, 14.3% husks, 12.3% cobs and 6.6% flowers, with up to 45% cellulose, 30% hemicellulose and 20% lignin. Further, due to its favorable economic and environmental potential, CS is considered an ideal raw material for producing biofuels and biobased chemicals, which can largely be divided into carbohydrate and lignin platforms. However, the techno-economic perspectives of CS-based biorefineries have remained questionable due to the inadequate supply chain logistics, lack of cost-effective conversion technologies, limited scale-up of the product-specific technologies, and lower competitiveness in the market compared to their counterparts, such as sugar and starch-based biorefineries. While CS is converted by thermochemical and biochemical approaches, the latter is considered to be more sustainable for its selective conversion under mild conditions using microorganisms. This review aimed to critically discuss the latest research and developments on the biochemical conversion of CS into biofuels and chemicals. In particular, this paper covers the market potential of biofuels and chemicals to which CS can make a significant contribution, technological developments in the microbial conversion of CS, major biofuels and chemicals produced from CS-derived carbohydrates and lignin, and the technoeconomic perspectives of CS-based biorefinery.

09 BIOMASS FUELS↗

Quantitative Determination of Biomass-derived Renewable Carbon in Fuels from Coprocessing of Bio-oils in Refinery Using a Stable Carbon Isotopic Approach

Increasing renewable carbon incorporation into conventional fuels through coprocessing with vacuum gas oil (VGO, a petroleum refining feedstock) is a critical step in biofuels development, scaling-up, adoption and associated GHG reduction. Optimization of the co-processing parameters maximizes incorporation of the renewable carbon in the fuel products. Quantitative determination of the renewable carbon content in the co-processed products provides direct evaluation of the parameters. The co-processing bio-oil with VGO through hydrocracking (HC) or fluid catalytic cracking (FCC) system resulted in carbon isotopic fractionation that prevented the direct use of the isotope mixing model for quantifying the renewable carbon. Here, we report an algorithm of using a stable carbon isotope approach to quantify the renewable carbon content in co-processing biofuel products through high-precision ?13C analysis. A controlled experiment carried out by blending a fossil diesel (-29.013‰) with a bio-diesel (-30.099‰) at various blending levels up to 98.0/2.0 wt% is presented and has demonstrated the applicability of this approach. The carbon isotope fractionation factors for the bio-oil co-processing were obtained by using a 14C-derived isotope-mixing model. The ?13C method was tested by co-processing 13C-labeled bio-crude and natural woody biomass-derived fast pyrolysis (FP) and catalytic fast pyrolysis (CFP) bio-oils with VGO. The results were verified by 14C accelerator mass spectrometry (AMS) method (ASTM-D6866) and compared with the yield mass balance (YMB) method. Strong agreement between d13C and 14C AMS methods demonstrated the applicability of the ?13C method to quantify renewable carbon content in co-processing fuel products and guide the co-processing optimization

Li, Zhenghua↗

Modeling the Economic and Environmental Impacts of Land Scarcity Under Deep Uncertainty

Abstract Land scarcity is increasing over time, driven by complex multisector dynamics. The impacts of land scarcity on the economy and environment are multi‐faceted and regional, so any action to convert land will contain inherent tradeoffs. These impacts are complicated by the deeply uncertain evolution of the various sectors influencing land scarcity. A need therefore exists to provide multi‐metric and multi‐sector assessments that are robust to myriad uncertainties. Land conservation effectively limits the supply of productive land, while biofuel consumption increases the demand and competition for that land, and how these dynamics individually and jointly propagate to economic and environmental impacts is an important open question. To address this, we adopt the Global Change Analysis Model (GCAM) that has representations of various important systems including the climate, macroeconomic, energy, agriculture and land, and water resources systems. Various scenarios of increased land demand (from biofuels) and decreased land supply (from conservation) under various socioeconomic scenarios drawn from the SSPs were simulated using GCAM. We find that while biofuel consumption and land conservation reduce carbon emissions, this comes at the cost of higher food prices, reduced crop production, and increased water withdrawals. Additionally, some regions experience these tradeoffs more severely than others and are more heavily impacted from the same biofuel mandate or by an additional percent of protected land. These and other findings highlight the importance of multisector modeling frameworks that capture many cross‐sector linkages, and acknowledge the important uncertainties confronting the human‐Earth system when making any analysis of land scarcity impacts.

54 ENVIRONMENTAL SCIENCES↗

n-Butanol production by Rhodopseudomonas palustris TIE-1

Anthropogenic carbon dioxide (CO 2 ) release in the atmosphere from fossil fuel combustion has inspired scientists to study CO 2 to biofuel conversion. Oxygenic phototrophs such as cyanobacteria have been used to produce biofuels using CO 2 . However, oxygen generation during oxygenic photosynthesis adversely affects biofuel production efficiency. To produce n-butanol (biofuel) from CO 2 , here we introduce an n-butanol biosynthesis pathway into an anoxygenic (non-oxygen evolving) photoautotroph, Rhodopseudomonas palustris TIE-1 (TIE-1). Using different carbon, nitrogen, and electron sources, we achieve n-butanol production in wild-type TIE-1 and mutants lacking electron-consuming (nitrogen-fixing) or acetyl-CoA-consuming (polyhydroxybutyrate and glycogen synthesis) pathways. The mutant lacking the nitrogen-fixing pathway produce the highest n-butanol. Coupled with novel hybrid bioelectrochemical platforms, this mutant produces n-butanol using CO 2 , solar panel-generated electricity, and light with high electrical energy conversion efficiency. Overall, this approach showcases TIE-1 as an attractive microbial chassis for carbon-neutral n-butanol bioproduction using sustainable, renewable, and abundant resources.

60 APPLIED LIFE SCIENCES↗

Tools for genetic engineering and gene expression control in Novosphingobium aromaticivorans and Rhodobacter sphaeroides

ABSTRACT Alphaproteobacteria have a variety of cellular and metabolic features that provide important insights into biological systems and enable biotechnologies. For example, some species are capable of converting plant biomass into valuable biofuels and bioproducts that have the potential to contribute to the sustainable bioeconomy. Among the Alphaproteobacteria, Novosphingobium aromaticivorans , Rhodobacter sphaeroides , and Zymomonas mobilis show promise as organisms that can be engineered to convert extracted plant lignin or sugars into bioproducts and biofuels. Genetic manipulation of these bacteria is needed to introduce engineered pathways and modulate expression of native genes with the goal of enhancing bioproduct output. Although recent work has expanded the genetic toolkit for Z. mobilis , N. aromaticivorans and R. sphaeroides still need facile, reliable approaches to deliver genetic payloads to the genome and to control gene expression. Here, we expand the platform of genetic tools for N. aromaticivorans and R. sphaeroides to address these issues. We demonstrate that Tn 7 transposition is an effective approach for introducing engineered DNA into the chromosome of N. aromaticivorans and R. sphaeroides . We screen a synthetic promoter library to identify isopropyl β-D-1-thiogalactopyranoside-inducible promoters with regulated activity in both organisms (up to ~15-fold induction in N. aromaticivorans and ~5-fold induction in R. sphaeroides ). Combining Tn 7 integration with promoters from our library, we establish CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) interference systems for N. aromaticivorans and R. sphaeroides (up to ~10-fold knockdown in N. aromaticivorans and R. sphaeroides ) that can target essential genes and modulate engineered pathways. We anticipate that these systems will greatly facilitate both genetic engineering and gene function discovery efforts in these species and other Alphaproteobacteria. IMPORTANCE It is important to increase our understanding of the microbial world to improve health, agriculture, the environment, and biotechnology. For example, building a sustainable bioeconomy depends on the efficient conversion of plant material to valuable biofuels and bioproducts by microbes. One limitation in this conversion process is that microbes with otherwise promising properties for conversion are challenging to genetically engineer. Here we report genetic tools for Novosphingobium aromaticivorans and Rhodobacter sphaeroides that add to the burgeoning set of tools available for genome engineering and gene expression in Alphaproteobacteria. Our approaches allow straightforward insertion of engineered pathways into the N. aromaticivorans or R. sphaeroides genome and control of gene expression by inducing genes with synthetic promoters or repressing genes using CRISPR interference. These tools can be used in future work to gain additional insight into these and other Alphaproteobacteria and to aid in optimizing yield of biofuels and bioproducts.

Hall, Ashley N.↗

Smart Preprocessing & Robust Integration Emulator

To achieve the desired particle size of biomass feedstocks during preprocessing for trouble-free handling and conversion to produce biofuels and bioproducts, the raw materials must undergo a crucial milling process. The particle size of biomass plays a critical role in subsequent biofuel manufacturing, where a larger area-to-volume ratio facilitates efficient synthesis while balancing the impact of moisture on biomass storage. To optimize biofuel production efficiency and overcome these challenges, it is imperative to accurately predict the particle size distribution (PSD) of the biomass in the design of efficient preprocessing systems. The population balance model (PBM), upon empirical calibration and validation, can provide rapid prediction of post-milling PSD of granular biomass. However, PSD has limitations related to mass conservation and the absence of moisture considerations. To overcome these drawbacks, a deep learning model called the enhanced deep neural operator (DNO+) is implemented in the code. This model not only retains the capabilities of the PBM in handling complex mapping functions but also incorporates additional factors influencing the system. By considering various experimental conditions such as sieve size and moisture content, the trained DNO+ model can effectively predict the PSD after milling for any given feed PSD. To further reduce the reliance on experimental data, the PBM is integrated into the DNO+ model, resulting in a physics-informed DNO+ (PIDNO+). The PIDNO+ model addresses the non-conservation of quality exhibited by the PBM while inheriting the advantages of the DNO+ model in considering multiple influencing factors. Moreover, the PIDNO+ model significantly reduces the amount of data required for model training. Both deep learning models, i.e., DNO+ and PIDNO+, are excellent in predictive performance, offering swift and accurate machine learning-based predictions. The use of this code that contains these models will assist in guiding the proper milling equipment selection and operational conditions to achieve the desired biomass particle sizes, ensuring the efficiency of subsequent biofuel and bioproduct production processes.

Xia, Yidong [Idaho National Laboratory (INL), Idah↗

Data for Optimizing Chemical-Free Pretreatment for Maximizing Oil/Lipid Recovery from Transgenic Bioenergy Crops and its Rapid Analysis Using Time Domain-NMR

Transgenic bioenergy crops have shown the potential to produce vegetative oil by accumulating energy-rich triacylglyceride molecules that can be converted into biofuels (biodiesel and biojet). These transgenic crops cater to improved biofuel yield by providing lipids along with cellulosic sugars. Efficient bioprocessing technologies are needed to utilize these transgenic plants to their maximum potential. To this end, this study investigates a low- and high-severity chemical-free hydrothermal pretreatment of transgenic oilcane 1566 bagasse with in situ lipids to maximize the recovery of lipids for biodiesel and fermentable sugars for ethanol with minimal inhibitor generation. Hydrothermal pretreatment at 170°C recovered ∼25% of total lipids in the pretreatment liquor, leaving the remainder in bagasse residue for hexane recovery post fermentation. The recovery of lipids in pretreatment liquor remained constant beyond 170°C. Along with lipids, ∼35% w/w and ∼50% w/w fermentable sugars were recovered post saccharification from bagasse pretreated at 170°C and 210°C for 20 min, respectively. Hydrothermal pretreatment at 170°C for 20 min provided the optimum conditions for maximum recovery of lipids and cellulosic sugars that resulted in enhanced biofuel yield per unit biomass. High severity pretreatment increased the generation of inhibitors beyond the tolerance of fermentation microorganisms. In addition, the application of time-domain proton NMR spectroscopy was extended to bioprocessing. NMR technology facilitated the analysis of total lipids, the composition of fatty acids, and the characterization of free and bound lipids in untreated and pretreated oilcane 1566 bagasse subsequent to each step of biomass to biofuel conversion.

Conversion↗

Data for Hydrothermal Conditioning of Oleaginous Yeast Cells to Enable Recovery of Lipids as Potential Drop-in Fuel Precursors

Lipids produced using oleaginous yeast cells are an emerging feedstock to manufacture commercially valuable oleochemicals ranging from pharmaceuticals to lipid-derived biofuels. Production of biofuels using oleaginous yeast is a multistep procedure that requires yeast cultivation and harvesting, lipid recovery, and conversion of the lipids to biofuels. The quantitative recovery of the total intracellular lipid from the yeast cells is a critical step during the development of a bioprocess. Their rigid cell walls often make them resistant to lysis. The existing methods include mechanical, chemical, biological and thermochemical lysis of yeast cell walls followed by solvent extraction. In this study, an aqueous thermal pretreatment was explored as a method for lysing the cell wall of the oleaginous yeast Rhodotorula toruloides for lipid recovery. Hydrothermal pretreatment for 60 min at 121 °C with a dry cell weight of 7% (w/v) in the yeast slurry led to a recovery of 84.6 ± 3.2% (w/w) of the total lipids when extracted with organic solvents. The conventional sonication and acid-assisted thermal cell lysis led to a lipid recovery yield of 99.8 ± 0.03% (w/w) and 109.5 ± 1.9% (w/w), respectively. The fatty acid profiles of the hydrothermally pretreated cells and freeze-dried control were similar, suggesting that the thermal lysis of the cells did not degrade the lipids. This work demonstrates that hydrothermal pretreatment of yeast cell slurry at 121 °C for 60 min is a robust and sustainable method for cell conditioning to extract intracellular microbial lipids for biofuel production and provides a baseline for further scale-up and process integration.

Conversion↗

Data for Greenhouse Gas Accounting Procedures in Low Carbon Fuel Policies Overlook the Spatial Variability of Miscanthus-Derived Sustainable Aviation Fuel

Low carbon fuel policies such as the U.S. Renewable Fuel Standard (RFS), Canada Clean Fuel Regulations (CFR), and California Low Carbon Fuel Standard (LCFS) as well as the 45Z tax credit are intended to reduce greenhouse gas (GHG) emissions from transportation. Cellulosic feedstocks, optimized biorefineries, and favorable farming locations can significantly reduce biofuel carbon intensity (CI). Despite advances in field-to-fuel GHG monitoring and flexibility in resource allocation within biorefineries (e.g., governing net electricity production), rigid CI accounting procedures in current policies may limit CI responsiveness across candidate sites and processing facilities. This work examines a hypothetical biomass-to-sustainable aviation fuel (SAF) pathway using miscanthus and alcohol-to-jet (i) to demonstrate how GHG accounting requirements drive estimates of biofuel CIs and (ii) to explore potential CI and financial implications of scenario-specific life cycle assessment (LCA). Results demonstrate that GHG accounting using the CFR/LCFS can reasonably account for distinct levels of net electricity production by a biorefinery, but only the CFR yields similar CI sensitivity to spatially explicit factors (feedstock CI, grid electricity CI) as scenario-specific LCA: most GHG accounting frameworks do not capture CI variation across candidate sites in the United States. Ultimately, this work demonstrates the importance of LCA methodological specifications in low carbon fuel policies and tax credits.

Miscanthus↗

Supply Chain Sustainability Analysis of Renewable Hydrocarbon Fuels via Indirect Liquefaction, Ex Situ Catalytic Fast Pyrolysis, Hydrothermal Liquefaction, Combined Algal Processing, and Biochemical Conversion: Update of the 2019 State-of-Technology Cases

This technical report describes the supply chain sustainability analysis (SCSAs) for the production of renewable hydrocarbon transportation fuels via a range of conversion technologies: (1) renewable high octane gasoline (HOG) via indirect liquefaction (IDL) of woody lignocellulosic biomass (note that the IDL pathway in this SCSA represents the syngas conversion design in the 2019 SOT); (2) renewable gasoline (RG) and diesel (RD) blendstocks via ex situ catalytic fast pyrolysis of woody lignocellulosic biomass; (3) RD via hydrothermal liquefaction (HTL) of wet sludge from a wastewater treatment plant; (4) renewable hydrocarbon fuels via biochemical conversion of herbaceous lignocellulosic biomass; (5) renewable diesel via HTL of a blend of algae and woody biomass; and (6) renewable diesel via combined algae processing (CAP). This technical report focuses on the environmental performance of these six biofuel production pathways in their 2019 SOT cases. The results of these renewable hydrocarbon fuel pathways in these SCSA analyses update those for the respective 2018 SOT cases. They also provide an opportunity to examine the impact of technology improvements in both biomass feedstock production and biofuel production that have been achieved in 2019 SOTs on the sustainability performance of these renewable transportation fuels, and they reflect updates to Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model, which was released in October 2019. These GREET updates include the production of natural gas, electricity, and petroleum-based fuels that can influence biofuels’ supply chain greenhouse gas (GHG) (CO₂, CH₄, and N₂O) emissions, water consumption, and air pollutant emissions. GHG emissions, water consumption, and nitrogen oxides (NO x ) emissions are the main sustainability metrics assessed in this analysis. In this analysis, we define water consumption as the amount of water withdrawn from a freshwater source that is not returned (or returnable) to a freshwater source at the same level of quality. Life-cycle fossil energy consumption and net energy balance, which is the life-cycle fossil energy consumption deducted from the renewable biofuel energy produced, are also assessed.

09 BIOMASS FUELS↗

Supply Chain Sustainability Analysis of Renewable Hydrocarbon Fuels via Indirect Liquefaction, Ex Situ Catalytic Fast Pyrolysis, Hydrothermal Liquefaction, Combined Algal Processing, and Biochemical Conversion: Update of the 2020 State-of-Technology Cases

This technical report describes the SCSAs for the production of renewable hydrocarbon transportation fuels via a range of conversion technologies in the 2020 SOTs: (1) renewable high octane gasoline (HOG) via indirect liquefaction (IDL) of woody lignocellulosic biomass (note that the IDL pathway in this SCSA represents the syngas conversion design); (2) renewable gasoline (RG) and diesel (RD) blendstocks via ex situ catalytic fast pyrolysis of woody lignocellulosic biomass; (3) RD via hydrothermal liquefaction (HTL) of wet sludge from a wastewater treatment plant; (4) renewable hydrocarbon fuels via biochemical conversion of herbaceous lignocellulosic biomass; (5) renewable diesel via HTL of a blend of algae and woody biomass; and (6) renewable diesel via combined algae processing (CAP). This technical report focuses on the environmental performance of these six biofuel production pathways in their 2020 SOT cases. The results of these renewable hydrocarbon fuel pathways in these SCSA analyses update those for the respective 2019 SOT cases. They also provide an opportunity to examine the impact of technology improvements in both biomass feedstock production and biofuel production that have been achieved in 2020 SOTs on the sustainability performance of these renewable transportation fuels. The SCSA results also reflect updates to Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET ® ) model, which was released in October 2020. These GREET updates include the production of natural gas, electricity, and petroleum-based fuels that can influence biofuels’ supply chain greenhouse gas (GHG) (CO 2 , CH 4 , and N 2 O) emissions, water consumption, and air pollutant emissions. GHG emissions, water consumption, and nitrogen oxides (NO x ) emissions are the main sustainability metrics assessed in this analysis. In this analysis, we define water consumption as the amount of water withdrawn from a freshwater source that is not returned (or returnable) to a freshwater source at the same level of quality. Life-cycle fossil energy consumption and net energy balance, which is the life-cycle fossil energy consumption deducted from the renewable biofuel energy produced, are also assessed.

09 BIOMASS FUELS↗

Assessing Nutrient and Carbon Responses to Agricultural Conservation Practices in Two Midwest Watersheds

The United States is undertaking efforts to transition to a low-carbon economy in response to the heightened impacts of climate change, which are largely attributed to decades of carbon-intensive development. A concerted effort by the energy sector to achieve net-zero carbon emissions is aimed at strategically reducing the carbon footprint of the energy supply chain, particularly in the production of feedstocks for biofuels. The production of biofuels relies heavily on land use and management practices in biomass cultivation. Among other factors, soil organic carbon (SOC) plays a crucial role in the biofuel carbon cycle, impacting land productivity, greenhouse gas emissions, and water quality. The process of carbon drawdown during plant growth and storage helps to mitigate the release of carbon dioxide (CO 2 ) into the atmosphere. Another key parameter is the release of nitrous oxide (N 2 O) — a potent greenhouse gas with a global warming potential 273 times that of CO 2 — from soil. While prioritizing low-carbon production, sustainable bioenergy also necessitates improved water quality and ecosystem services. Agricultural conservation practices can contribute to enhanced soil health and reduce nutrient and sediment loss into streams. However, studies that explore the broader impact of these practices on soil carbon storage and N 2 O emissions at a watershed scale are limited. Specifically, our understanding of how low-carbon feedstock production and management affect nutrient cycle dynamics is incomplete. This study assesses watershed responses to land management practices in two agriculturally dominant watersheds: the Raccoon River watershed and the Southfork of Iowa River watershed. The study focuses on carbon and nutrient dynamics, characterizing spatial and temporal variations in SOC, N 2 O, and nutrient loadings to examine the relationship between nutrient and carbon responses and agricultural conservation practices. The study employs the newly developed Soil Water Analysis Tool for Carbon (SWAT-C) model, calibrated using 20 years’ of climate and water monitoring data, to simulate and evaluate two agricultural conservation practices: no-till and crop residue harvest with cover crop planting. We compared the calibrated SWAT-C model with a historical baseline model, which allowed us to analyze various aspects of the watershed, including stream flow, suspended sediments, nitrogen, phosphorus, organic carbon, SOC at different depths, and N 2 O emissions from topsoil. Our SWAT-C modeling results indicate that, compared with results from the historical baseline model, no-till practices are positively correlated with SOC accumulation, reduced N 2 O emissions, and decreased soil loss. We also observed no change or slightly increased nitrogen and phosphorus loss to water bodies in the watersheds compared with the baseline. Conversely, crop residue harvest with cover crop planting improved water quality by reducing nutrient and soil losses but also increased N 2 O emissions. This SWAT-C modeling study establishes the groundwork for further smaller-scale and/or sub-basin-level assessments of nitrogen, phosphorus, and carbon cycles. It provides valuable science-based insights to inform policy decisions — particularly in the context of transitioning to biofuel feedstock production in these watersheds — by addressing concerns about nutrient exports to local water bodies and, ultimately, the Mississippi River.

54 ENVIRONMENTAL SCIENCES↗

Pilot-Scale Algal Oil Production

The main objective of the project is complete: development of a preliminary planning and design for a pilot-scale algal oil cultivation and processing facility, FEL-3 design with -5% / +15% cost estimate accuracy, and conversion of the algal oil to biofuel in an off-site existing bio-oil refinery. The design basis includes 10 tons per day of dried algae cultivated with CO 2 supplied by direct air capture, electricity supplied solar power, well water supply, zero liquid discharge, off-site extraction, and off-site conversion of oil to biofuel. The design and permitting package is an important milestone in the path to commercialization of algal biofuels and bioproducts as it provides the preliminary design, permitting path, long-term land lease, planning documents, and team needed for success in future engineering, construction, start-up and operations of a pilot-scale farm at a site in Paso Robles, CA. Outcomes of the business assessment include (i) identification of a product spectrum for economical algal biofuels using co-products with markets that are commensurate with production of 6-7 billion gallons per year of sustainable aviation fuel (SAF), renewable diesel, and renewable gasoline, (ii) a path toward near-term contribution of algae oil to SAF, and (iii) an approach for long-term operation of a pilot-scale farm.

09 BIOMASS FUELS↗

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↗