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At least 109 records · Page 6

Using waste CO 2 from corn ethanol biorefineries for additional ethanol production: life‐cycle analysis

Abstract Corn ethanol plants generate high‐purity carbon dioxide (CO 2 ) while producing ethanol. If that CO 2 could be converted into ethanol by carbon capture and utilization technologies it would be possible to increase ethanol production more than 37% without additional corn grain inputs. Gas fermentation processes use microbes to convert carbon‐containing gases into ethanol and so have the potential to be used with the CO 2 from biorefineries for this purpose. However, as CO 2 utilization technologies for converting thermodynamically stable CO 2 are typically energy intensive, it is necessary to evaluate the related life‐cycle greenhouse gas (GHG) emissions (carbon intensities or CIs) to see whether there are actual emission reduction benefits. In this study, we evaluate the CIs of ethanol produced from high‐purity CO 2 in corn ethanol plants by gas fermentation plus electrochemical reduction. Our analysis shows that the sources of electricity and hydrogen are key drivers of CO 2 ‐based ethanol's GHG emissions. With wind electricity, the design cases show the potential of near‐zero CI ethanol (1.1 g CO 2 e/MJ), but that can increase to up to 331–531 g CO 2 e/MJ when today's U.S. Midwest electricity mix is used. To avoid the renewable electricity intermittency issue, we considered a power purchase agreement option using wind electricity 40% of the time and using the regional mix for the rest, which provides a 42% GHG emission reduction from the CI of gasoline. © 2020 The Authors and UChicago Argonne, LLC, Operator of Argonne National Laboratory. Biofuels, Bioproducts and Biorefining published by Society of Chemical Industry and John Wiley & Sons, Ltd.

09 BIOMASS FUELS↗

Predictive models enhance feedstock quality of corn stover via air classification

Feedstock heterogeneity is a fundamental obstacle to cost-competitive biobased products. Agricultural products like corn stover have anatomical components that vary in their chemical composition, mechanical properties, structure, and response to chemical and biological treatments. A technique that can enrich streams in select anatomical fractions would allow a tailored deconstruction approach to increase overall process efficiency. Air classification can be leveraged for such refining, however, fundamental characterization and understanding of the particle properties that underly the physics of air classification are only modestly documented. Here, we determine fundamental particle properties including mass-to-area ratio, drag coefficient, and partition velocity that describe how anatomical tissues of corn stover behave during air classification. In this work, mass-to-area ratios of anatomical tissues vary by nearly two orders of magnitude from 2.3 mg/mm 2 for cob to 0.04 mg/mm 2 for leaf. Drag coefficients of longer, fibrous materials (i.e., rind, husk, and sheath) are shown to correlate with particle area (p-value < 0.001) whereas granular tissues (i.e., cob, pith, and leaf) correlate better with mass-to-area ratio (p-values < 0.001). When compared to experimental observations, a simulated two-stage air classification and size reduction scenario predicts the overall partitioning of anatomical tissues within 15% for pith, husk, rind, and cob tissues. The model predicts an air-classified fraction preferentially enriched in cob (purity = 20%), rind (purity = 74%), and pith (purity = 4.5%) with a mass yield of 47%. Empirical relations for these properties can be used to predict the partitioning of corn stover during air classification based on anatomical type and size.

09 BIOMASS FUELS↗

An adaptive adversarial domain adaptation approach for corn yield prediction

Recently, statistical machine learning and deep learning methods have been widely explored for corn yield prediction. Though successful, machine learning models generated within a specific spatial domain often lose their validity when directly applied to new regions. To address this issue, we designed an unsupervised adaptive domain adversarial neural network (ADANN). Specifically, through domain adversarial training, the ADANN model reduced the impact of domain shift by projecting data from different domains into the same subspace. Also, the ADANN model was designed to be trained in an adaptive way, which guaranteed the model can learn the domain-invariant features and perform accurate yield prediction simultaneously. Informative variables including time-series vegetation indices and sequential weather observations were first collected from multiple data sources and aggregated to the county level. Then, we trained the ADANN model with the extracted features and corresponding reported county-level corn yield from the U.S. Department of Agriculture (USDA). Finally, the trained model was evaluated in four testing years 2016–2019. The U.S. corn belt was used as the study area and counties under study were grouped into two diverse ecological regions. Overall, the experimental results showed that the developed ADANN model had better performance than three other state-of-the-art machine learning models in both local experiments (train and test in the same region) and transfer experiments (train and test in different regions). As the first study using adversarial learning for crop yield prediction, this research demonstrates a novel solution for improving model transferability on crop yield prediction.

59 BASIC BIOLOGICAL SCIENCES↗

Microwave-assisted co-gasification of mixed plastics and corn stover: A synergistic approach to produce clean hydrogen

Co-gasification of waste plastic and corn stover into hydrogen is an effective way of reducing hydrogen cost and carbon footprint. However, current gasification technologies are energy intensive and cannot accommodate flexible feedstock. Microwave gasification offers several advantages including higher H 2 yield and enhanced selectivity to syngas over tars. Herein this work presents parametric optimization study of microwave co-gasification of mixed plastics and corn stover for hydrogen-rich syngas. High hydrogen yields of 30.5 mmol H2 /g feed at 700 °C were obtained using a microwave reactor, as opposed to 0.9 mmolH 2 /g feed at 700-950 °C with conventional heating. Hydrogen yields are >98% of the theoretical extractable hydrogen from feedstock. Microwaves enhanced plastic and corn stover synergy and reduced tar yields. H-poor carbon formation resulting from the dehydrogenation of tar and coke, and light olefins decomposition, triggered by the external microwave electric fields, allowed further cracking of intermediate hydrocarbons to produce additional H 2 .

30 DIRECT ENERGY CONVERSION↗

Characterizing value-added pellets obtained from blends of miscanthus, corn stover, and switchgrass

The current pellet industry primarily relies on woody biomass. Inclusion of a diverse feedstock, such as herbaceous biomass, is necessary to meet the rising demand for pellets in heat and power generation, and for biofuel production. This study was motivated by the need to densify biomass, improving its naturally low energy density, to reach the required pellet standards for biofuel conversion. Here, we developed value-added miscanthus pellets blended with different ratios of corn stover and switchgrass and analyzed their chemical, physical, and mechanical properties. Pure miscanthus pellet durability index (PDI) was less than 85 %, well below the ISO 17225-6 standard for herbaceous pellets. While increasing switchgrass and corn stover ratios increases durability beyond 94 %, it also increases ash content from 1.6 % to 4.6 %, a quality unfavorable for biofuel conversion. The moisture content of the blended pellets varied from 7.12 % to 12.45 %, and positively correlated with the durability of the pellets. Pure miscanthus pellets had the highest bulk density, 633 kg/m 3 , while pellets containing 75 % miscanthus and 25 % corn stover had the lowest density, 564 kg/m 3 . The findings of this study also identified a decrease in the pellet bulk density with the increase in ash content and pellet diameter.

09 BIOMASS FUELS↗

Projecting Life-Cycle Environmental Impacts of Corn Production in the U.S. Midwest under Future Climate Scenarios using machine learning approach

Emission factors and process-based mechanism models are popular approaches used to estimate life-cycle environmental impacts. However, emission factors are often incapable of describing spatial and temporal heterogeneity of agricultural emissions, whereas process-based mechanism models, capable of capturing the heterogeneity, tend to be very complicated, and time-consuming. Efficient predictions of life-cycle environmental impacts from agricultural production are lacking. This study develops a rapid predictive model to quantify life-cycle global warming (GW), eutrophication (EU) and acidification (AD) impacts of corn production using a novel machine learning approach. We used the boosted regression tree (BRT) model to estimate current and future life-cycle environmental impacts of corn production in 12 U.S. Midwest at county scale under four Intergovernmental Panel on Climate Change (IPCC)’s climate scenarios (RCP2.6. 4.5, 6.0, and 8.5) for years 2009-2100. Results show that future life-cycle GW, EU and AD impacts of corn production will increase under all four scenarios, with the worst environmental impacts shown under the RCP 8.5 scenario. Significant spatial variation were estimated to be 3.6, 29.9 and 1.8-folds under the RCP4.5 scenario, and 6.6, 152.9 and 1.6-folds under the RCP8.5 scenario, respectively. Findings from this study demonstrate the importance of considering county-level life-cycle environmental impacts and the influences of climate change in future years to aid in developing potential adaptation and mitigation programs and policies.

Machine learning, climate change, projections, env↗

Go with the Flow: Additives to Improve the Flowability of Crumbled Corn Stover

For this work, magnesium stearate (MgSt), a common flow additive and anticaking agent, was applied to corn stover feedstocks with three particle sizes. The material handling properties of dry, 15%, and 30% moisture content corn stover were measured with a Freeman FT-4 powder rheometer and mass flow hopper calculations. While hydrated biomass typically exhibits poor flowability, introducing MgSt led to a significant increase in flowability for dry and 15% moisture content feedstocks, with less impact at 30% moisture content. Inverse gas chromatography showed a decrease, up to 40%, in the surface energy of MgSt-coated corn stover. While MgSt may not be ideal for biofuel or chemical production, this study highlights the potential of flow additives to reduce adhesive and cohesive forces, improving biomass feedstock handling.

09 BIOMASS FUELS↗

Measured and Simulated Carbon Dynamics in Midwestern U.S. Corn‐Soybean Rotations

Abstract Corn ( Zea mays L.) and soybean ( Glycine max [L.] Merr.) production dominate Midwestern U.S. agriculture and impact the regional carbon and nitrogen cycles. Sustaining soil carbon is important for corn‐soybean production (CS); however, quantifying soil carbon changes requires long‐term field measurements and/or model simulations. In this study, changes in soil organic (SOC), inorganic (SIC), and total (TC) carbon; pH; total nitrogen (TN); and net ecosystem production (NEP) were measured in a conventional corn‐soybean rotation in central Iowa. Soil samples ( n = 42; 0–120 cm depth) were collected from two adjacent fields in 2005 and 2016. Eddy‐flux stations set up in the fields continuously monitored NEP from 2005–2016, and net biome production (NBP) was calculated using yield records. The DayCENT model was used to simulate the effects of conventional management practices on soil carbon and calibrated with field‐measured NEP and SOC. Measured soil TC (0–120 cm) decreased by −14.19 ± 6.25 Mg ha −1 , with highest reductions in SOC and SIC ( p < 0.05) at 0–15 and 90–120 cm, respectively. Measured TN decreased by −0.7 ± 0.29 Mg ha −1 with N‐accumulation at 60–90 cm ( p < 0.05). Eddy‐flux NBP decreased by −13.19 ± 0.05 Mg ha −1 . Soil and eddy‐flux records show a carbon reduction by −1.14 ± 0.63 and −1.20 ± 0.06 Mg ha −1 yr −1 , respectively. The validated DayCENT model suggests that all SOC pools declined. We postulate that conventional CS production has adverse effects on C and N dynamics in Midwestern United States.

Dold, C.↗

Substantial carbon loss respired from a corn–soybean agroecosystem highlights the importance of careful management as we adapt to changing climate

Understanding agroecosystem carbon (C) cycle response to climate change and management is vital for maintaining their long-term C storage. We demonstrate this importance through an in-depth examination of a ten-year eddy covariance dataset from a corn–corn–soybean crop rotation grown in the Midwest United States. Ten-year average annual net ecosystem exchange (NEE) showed a net C sink of –0.39 Mg C ha –1 yr –1 . However, NEE in 2014 and 2015 from the corn ecosystem was 3.58 and 2.56 Mg C ha –1 yr –1 , respectively. Most C loss occurred during the growing season, when photosynthesis should dominate and C fluxes should reflect a net ecosystem gain. Partitioning NEE into gross primary productivity (GPP) and ecosystem respiration (ER) showed this C 'burp' was driven by higher ER, with a 51% (2014) and 57% (2015) increase from the ten-year average (15.84 Mg C ha –1 yr –1 ). GPP was also higher than average (16.24 Mg C ha –1 yr –1 ) by 25% (2014) and 37% (2015), but this was not enough to offset the C emitted from ER. This increased ER was likely driven by enhanced soil microbial respiration associated with ideal growing season climate, substrate availability, nutrient additions, and a potential legacy effect from drought.

54 ENVIRONMENTAL SCIENCES↗

Corn stover harvest reduces soil CO 2 fluxes but increases overall C losses

Abstract Harvesting corn ( Zea mays L.) stover for use as bioenergy feedstock may provide short‐term economic benefits and perhaps improve grain yield in continuous corn systems, but excessive stover removal may lead to long‐term depletion of soil C stocks. To better quantify the impacts of stover harvest on the soil C balance, we investigated CO 2 fluxes under three harvest treatments (none, moderate, and high) in three continuous corn systems: (a) no tillage and no biochar applications, (b) chisel plowing with biochar amendments, and (c) chisel plowing without biochar amendments were quantified. We sampled static chambers 14, 13, and 15 times in 2010, 2011, and 2012, respectively, and the measurements were used to calibrate the Agricultural Production Systems sIMulator model. Although CO 2 ‐C emissions did not differ among the three systems, both moderate (approximately 30%) and high (approximately 60%) stover removal rates reduced simulated CO 2 ‐C emissions by nearly 10% and more than 22%, respectively. Despite these reductions in CO 2 flux, the sum of CO 2 ‐C and stover C exceeded CO 2 ‐C losses in those plots without stover removal. This finding suggested soil C depletion was occurring for the soil and crop management practices used, even though depletion was not evident after 3 years. Application of biochar increased soil C levels, suggesting it may be able to offset some C losses. We conclude that for sustainable, highly productive agroecosystems that include stover harvest, all agronomic practices must be optimized to minimize C losses and maintain soil quality.

54 ENVIRONMENTAL SCIENCES↗

Data from Technical and Economic Feasibility of an Integrated Ethanol and Anthocyanin Coproduction Process Using Purple Corn Stover

The coproduction of high-value anthocyanin extract in the cellulosic ethanol process would diversify the co-product market, increase revenue, and potentially improve the economics of the process. The high anthocyanin concentration in the cob and structural carbohydrates in residual stover make purple corn stover an attractive source for anthocyanin and ethanol coproduction. This study aimed to develop simulation models for processes integrating ethanol production and anthocyanin extraction using purple corn stover, to evaluate their techno-economic feasibility, and to compare their performance with the conventional ethanol production process using corn stover. The annual ethanol production for plants processing 2000 MT dry feedstock / day was 148.6 million L/year for the integrated processes compared with 222.6 million L/year for the conventional process. Anthocyanin production in the modified processes using dilute acid-based and water-based anthocyanin extraction processes was 1779 and 1099 MT/year, respectively. Capital investments for the integrated processes ($448.1 to $443.8 million) were higher than the conventional process ($371.9 million). Due to high revenue from anthocyanin extract, the ethanol production cost for the integrated process using acid-based anthocyanin extraction ($0.36/L) was 34.5% lower than conventional ethanol production ($0.55/L). The ethanol production cost for the integrated process using water-based anthocyanin extraction ($0.68/L) was higher than conventional ethanol production due to low ethanol and anthocyanin yields. The minimum ethanol selling price for the integrated process using acid-based anthocyanin extraction ($0.65/L) was also lower than the conventional process ($0.72/L), indicating an improvement in economic performance.

Conversion↗

AmeriFlux FLUXNET-1F US-RGA Arkansas Corn Farm

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RGA Arkansas Corn Farm. This is the FLUXNET version of the carbon flux data for the site US-RGA Arkansas Corn Farm produced by applying the standard ONEFlux (1F) software. Site Description - Commercially farmed corn-soy rotation in Arkansas County, Arkansas. Part of a multi-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project.

Schuppenhauer, Michael R.↗

AmeriFlux US-DS1 Staten Corn 1

This is the AmeriFlux version of the carbon flux data for the site US-DS1 Staten Corn 1. Site Description - This tower is located in a corn field in the California Delta on Staten Island. The tower is within several square kilometers of corn fields that comprise the vast majority of the southern and central portion of Staten Island

Christen, Nick↗

AmeriFlux US-DS2 Staten Corn 2

This is the AmeriFlux version of the carbon flux data for the site US-DS2 Staten Corn 2. Site Description - This tower is located in a corn field in the California Delta on Staten Island. The tower is positioned within several hundred hectares of homogenous agricultural (corn) fields.

Deverel, Steve↗

AmeriFlux FLUXNET-1F US-MN1 Morris: Corn-Soybean with Cover Crops, Strip Tillage

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MN1 Morris: Corn-Soybean with Cover Crops, Strip Tillage. This is the FLUXNET version of the carbon flux data for the site US-MN1 Morris: Corn-Soybean with Cover Crops, Strip Tillage produced by applying the standard ONEFlux (1F) software. Site Description - Cropland, 2-year rotation (corn-soybean), strip tillage with winter cover crops (annual rye), nutrient management by soil tests, uniform pest management, tile drainage

Helseth, Christina [USDA-ARS LTAR]↗

AmeriFlux FLUXNET-1F US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage. This is the FLUXNET version of the carbon flux data for the site US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage produced by applying the standard ONEFlux (1F) software. Site Description - Cropland, 3-year rotation (corn-soybean-wheat), cover crops (winter camelina and pennycress), minimum tillage, nutrient management by soil tests, uniform pest management, tile drainage

Helseth, Christina [USDA-ARS LTAR]↗

AmeriFlux FLUXNET-1F US-MN3 Morris: Corn-Soybean, Conventional Tillage

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MN3 Morris: Corn-Soybean, Conventional Tillage. This is the FLUXNET version of the carbon flux data for the site US-MN3 Morris: Corn-Soybean, Conventional Tillage produced by applying the standard ONEFlux (1F) software. Site Description - Cropland, 2-year rotation (corn-soybean), conventional (deep rip) tillage, uniform nutrient management, uniform pest management, tile drainage

Helseth, Christina [USDA-ARS LTAR]↗

Let’s Stick Together: Interplay of Moisture, Particle Size, and Anatomical Fraction in the Flowability of Corn Stover Crumbles

Handling of agricultural waste biomass feedstocks (such as corn stover) is a persistent challenge in the production of biofuels and chemicals at integrated biorefineries. Inconsistent flowability and high feedstock variability creates equipment downtime and processing challenges. This work investigates the influence of anatomical fractionation and moisture content on the bulk solids handling behavior of corn stover crumbles. A combination of rotational shear testing, tribological measurements, and surface and sorption characterization techniques (inverse gas chromatography (IGC), dynamic vapor sorption (DVS), and electron microscopy) were used to evaluate the contributions of particle composition, size, and surface properties to flow behavior. Shear and frictional testing revealed that moisture content has the greatest effect on flowability, significantly increasing unconfined yield strength (ƒ c ) and reducing the flow function coefficient (F F C), regardless of anatomical fraction. While differences in surface energy were observed between fractions, particularly in polar contributions (γ AB ), these did not correspond to meaningful differences in flow behavior. Coarser 6 mm particles exhibited poorer flow performance than 4 mm crumbles, likely due to broader particle size distributions and increased particle interlocking. Taken together, these results suggest that anatomical fractionation provides minimal benefit from a bulk handling perspective. Moisture content and particle size heterogeneity dominate handling behavior, reinforcing the utility of unfractionated corn stover in processing environments. These insights can inform the design of more efficient and reliable feedstock processing systems for agricultural biomass in integrated biorefineries.

09 BIOMASS FUELS↗