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Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗

Bioenergy pathways within United States net-zero CO 2 emissions scenarios in the Energy Modeling Forum 37 study

The Energy Modeling Forum 37 study is organized around carbon dioxide (CO 2 ) mitigation scenarios reaching net-zero CO 2 emissions by 2050 in the United States. Here, this paper summarizes the potential contribution of bioenergy use in the electric power, transportation, industrial, and buildings sectors toward meeting that target based on model results. Thirteen modeling teams reported bioenergy consumption in the Reference and Net Zero scenarios. Consumption of bioenergy increased over time in the Reference scenario, from an average across models of 3.2 exajoules (EJ) in 2020 to 3.8 EJ in 2050. Average bioenergy consumption in 2050 increased further to 7.3 EJ in the Net Zero scenario. All scenarios that reach net-zero emissions required some form of carbon dioxide removal to offset emissions that are difficult to reduce. Carbon dioxide removal using bioenergy with CO 2 capture and storage (BECCS) varies widely across models, up to 1000 Mt CO 2 in 2050. Some models rely instead on direct air carbon capture and storage (DACCS), up to 2200 Mt CO 2 , and others use a combination of BECCS and DACCS. Model results show a strong inverse relationship between the amounts of BECCS and DACCS deployed. All modeling teams assumed a carbon sink from land use, land use change, and forestry, further offsetting a portion of emissions from fossil fuels and industry that are expensive to eliminate. Bioenergy consumption in 2050 decreased by an average of 1.5 EJ across eight models in a Net Zero+ scenario relative to the Net Zero scenario, due in part to a lower equilibrium carbon price resulting from optimistic cost assumptions for all energy technologies.

09 BIOMASS FUELS↗

Reparameterizing Litter Decomposition Using a Simplified Monte Carlo Method Improves Litter Decay Simulated by a Microbial Model and Alters Bioenergy Soil Carbon Estimates

Litter decomposition determines soil organic matter (SOM) formation and plant-available nutrient cycles. Therefore, accurate model representation of litter decomposition is critical to improving soil carbon (C) projections of bioenergy feedstocks. Soil C models that simulate microbial physiology (i.e., microbial models) are new to bioenergy agriculture, and their parameterization is often based on small datasets or manual calibration to reach benchmarks. Here, we reparameterized litter decomposition in a microbial soil C model (CORPSE - Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment) using the continental-scale Long-term Inter-site Decomposition Experiment Team (LIDET) dataset which documents decomposition across a range of litter qualities over a decade. Here, we conducted a simplified Monte Carlo simulation that constrained parameter values to reduce computational costs. The LIDET-derived parameters improved modeled C and nitrogen (N) remaining, decomposition rates, and litter mean residence times as compared to Baseline parameters. We applied the LIDET litter decomposition parameters to a microbial bioenergy model (Fixation and Uptake of Nitrogen – Bioenergy Carbon, Rhizosphere, Organisms, and Protection) to examine soil C estimates generated by Baseline and LIDET parameters. LIDET parameters increased estimated soil C in bioenergy feedstocks, with even greater increases under elevated plant inputs (i.e., by increasing residue, N fertilization). This was due to the integrated effects of plant litter quantity, quality, and agricultural practices (tillage, fertilization). Collectively, we developed a simple framework for using large-scale datasets to inform the parameterization of microbial models that impacts projections of soil C for bioenergy feedstocks.

54 ENVIRONMENTAL SCIENCES↗

Albedo-induced global warming impact of Conservation Reserve Program grasslands converted to annual and perennial bioenergy crops

Abstract Climate benefit assessments of bioenergy crops often focus on biogeochemical impacts, paying little if any attention to biogeophysical impacts. However, land conversions required for large-scale bioenergy crop production are substantial and may directly affect the climate by altering surface energy balance. In the US, such land conversions are likely to be met in part by converting Conservation Reserve Program (CRP) grassland to bioenergy crops. Here, we converted three 22 year old CRP smooth brome grass fields into no-till corn, switchgrass, or restored prairie bioenergy crops. We assessed the biogeophysical climate impact of the conversions using albedo changes relative to unconverted reference CRP grassland. The corn and perennial fields had higher annual albedo than the grassland they replaced—causing cooling of the local climate. The cooling of the corn field occurred solely during the non-growing season—especially when surfaces were snow-covered, whereas the cooling of the perennial fields was more prominent during the growing season. Compared to biogeochemical impacts with fossil fuel offsets for the same land conversions over eight years, the annual albedo-induced climate benefits add ∼35% and ∼78% to the annual biogeochemical benefits provided from the switchgrass and restored prairie fields, respectively, and offset ∼3.3% of the annual greenhouse gas (GHG) emissions from the corn field. We conclude that albedo-induced climate mitigation from conversion of CRP lands to perennial but not annual bioenergy crops can be substantial, and future climate impact assessments of bioenergy crops should include albedo changes in addition to GHG balances in order to better inform climate policies.

54 ENVIRONMENTAL SCIENCES↗

Redefining marginal land for bioenergy crop production

Abstract Marginal land has received wide attention for its potential to produce bioenergy feedstocks while minimizing diversion of productive agricultural land from food crop production. However, there has been no consensus in the literature on how to define or identify land that is marginal for food crops and beneficial for bioenergy crops. Studies have used different definitions to quantify the amount of such land available; these have largely been based on assumed biophysical thresholds for soil quality and productivity that are unchanging over space and time. We discuss the limitations of these definitions and the rationale for considering economic returns and environmental outcomes in classifying land as marginal. We then propose the concept of “socially” marginal which is defined as land that is earning close to zero returns after accounting for the monetized costs of environmental externalities generated. We discuss a broad set of criteria for classifying land as socially marginal for food crops and suitable for bioenergy crops; with these criteria, this classification depends on spatially varying and time‐varying factors, such as climate and market conditions and policy incentives. While there are challenges related to identifying this marginal land, satellite and other large‐scale datasets increasingly enable such analysis at a fine spatial resolution. We also discuss reasons why landowners might choose not to convert bioenergy‐suitable land to bioenergy crops, and thus the need for policy incentives to support conversion of land that is socially beneficial for bioenergy crop production.

09 BIOMASS FUELS↗

Identification of pleiotropic loci mediating structural and non-structural carbohydrate accumulation within the sorghum bioenergy association panel using high-throughput markers

Molecular characterization of diverse germplasm can contribute to breeding programs by increasing genetic gain for sorghum [ Sorghum bicolor (L.) Moench] improvement. Identifying novel marker-trait associations and candidate genes enriches the existing genomic resources and can improve bioenergy-related traits using genomic-assisted breeding. In the current scenario, identifying the genetic loci underlying biomass and carbon partitioning is vital for ongoing efforts to maximize each carbon sink’s yield for bioenergy production. Here, we have processed a high-density genomic marker (22 466 550) data based on whole-genome sequencing (WGS) using a set of 365 accessions from the bioenergy association panel (BAP), which includes ~19.7 million (19 744 726) single nucleotide polymorphism (SNPs) and 2.7 million (~2 721 824) insertion deletions (indels). A set of high-quality filtered SNP (~5.48 million) derived markers facilitated the assessment of population structure, genetic diversity, and genome-wide association studies (GWAS) for various traits related to biomass and its composition using the BAP. The phenotypic traits for GWAS included seed color (SC), plant height (PH), days to harvest (DTH), fresh weight (FW), dry weight (DW), brix content % (BRX), neutral detergent fiber (NDF), acid detergent fiber (ADF), non-fibrous carbohydrate (NFC), and lignin content. Several novel loci and candidate genes were identified for bioenergy-related traits, and some well-characterized genes for plant height ( Dw1 and Dw2 ) and the YELLOW SEED1 locus ( Y1 ) were validated. We further performed a multi-variate adaptive shrinkage analysis to identify pleiotropic QTL, which resulted in several shared marker-trait associations among bioenergy and compositional traits. Significant marker-trait associations with pleiotropic effects can be used to develop molecular markers for trait improvement using a marker-assisted breeding approach. Significant nucleotide diversity and heterozygosity were observed between photoperiod-sensitive and insensitive individuals of the panel. This diverse bioenergy panel with genomic resources will provide an excellent opportunity for further genetic studies, including selecting parental lines for superior hybrid development to improve biomass-related traits in sorghum.

bioenergy association panel↗

Climate Forcing of Bioenergy Feedstocks: Insights From Carbon and Energy Flux Measurements

Bioenergy from biofuels has the potential to slow growing atmospheric carbon dioxide concentrations by reducing fossil fuel use. However, growing bioenergy feedstocks is a land-intensive process. In the United States, the recent expansion of maize bioethanol has presented some environmental costs, prompting the development of several alternative bioenergy feedstocks. These feedstocks, selected in part for traits associated with ecosystem services, may provide opportunities for environmental benefits beyond fossil fuel displacement. We hypothesized that these bioenergy ecosystems will provide direct climatic cooling through their influence on carbon and radiative energy fluxes (i.e., through albedo). To test this hypothesis, we investigated the potential cooling effect of five current or potential bioenergy feedstocks using multi-year records from eddy covariance towers. Perennial feedstocks were carbon sinks, with an annual mean net ecosystem carbon balance (NECB) of –2.7 ± 2.1 Mg C ha –1 for miscanthus, –0.8 ± 1.1 Mg C ha –1 for switchgrass, and –1.4 ± 0.7 Mg C ha –1 for prairie. In contrast, annual rotations were generally carbon sources, with an annual mean NECB of 2.6 ± 2.4 Mg C ha –1 for maize-soy and 3.2 ± 2.1 Mg C ha –1 for sorghum-soy. Using maize-soy as a baseline, conversion to alternative feedstocks increased albedo, inducing further cooling. This effect was strongest for miscanthus, with –3.5 ± 2.0 W m –2 of radiative forcing, and weakest for sorghum, with –1.4 ± 1.4 W m –2 . When feedstock effects on carbon and albedo were compared using carbon equivalents, carbon fluxes were the stronger ecosystem effect, underscoring the role of perennial species as effective carbon sinks. This work highlights the impact of feedstock choice on ecosystem processes as an element of bioenergy land conversion strategies.

09 BIOMASS FUELS↗

Future bioenergy expansion could alter carbon sequestration potential and exacerbate water stress in the United States

The maximum future projected bioenergy expansion potential, in scenarios limiting warming to 2°C or below, is equivalent to half of present-day croplands. We quantify the impacts of large-scale bioenergy expansion against re/afforestation, which remain elusive, using an integrated human-natural system modeling framework with explicit representation of perennial bioenergy crops. The end-of-century net carbon sequestration due to bioenergy deployment coupled with carbon capture and storage largely depends on fossil fuel displacement types, ranging from 11.4 to 31.2 PgC over the conterminous United States. These net carbon sequestration benefits are inclusive of a 10 PgC carbon release due to land use conversions and a 2.4 PgC loss of additional carbon sink capacity associated with bioenergy-driven deforestation. Moreover, nearly one-fourth of U.S. land areas will suffer severe water stress by 2100 due to either reduced availability or deteriorated quality. These broader impacts of bioenergy expansion should be weighed against the costs and benefits of re/afforestation-based strategies.

09 BIOMASS FUELS↗

Bioenergy Cropping Reduces the Spatiotemporal Scaling of Soil Bacterial Biodiversity

Widespread bioenergy cropping can transform landscapes, strongly affecting biodiversity. However, the impact of bioenergy cropping on the spatiotemporal scaling of soil biodiversity remains virtually unknown, despite its profound implications for the functioning of the ecological community. Here, we investigated how bioenergy cropping influenced the spatiotemporal scaling of soil bacterial biodiversity in marginal soils (sandy loam and clay loam soils) in Oklahoma, USA. We detected strong, significant species-time-area relationships (STARs) and phylogenetic-time-area relationships (PTARs) in bacterial communities and their lineages, suggesting that STARs and PTARs exist in microbial ecology within the studied system. Also, spatiotemporal scaling rates (the slopes of STAR and PTAR models) varied substantially among bacterial lineages and were positively correlated with their 16S rRNA gene copy numbers, a genomic trait indicative of microbial growth potentials. Strikingly, bioenergy cropping significantly reduced spatiotemporal scaling rates by 6.8%-14.1%, with a more pronounced reduction observed in sandy loam soils, where those rates were significantly lower than in clay loam soils. The heterogeneity of soil phosphorus and carbon resulted in variations in bacterial spatiotemporal scaling rates. Collectively, our findings suggest that bioenergy cropping may alleviate rapid shifts in soil biodiversity across space and time, thereby stabilizing soil biodiversity and supporting its role as part of sustainable land management and climate mitigation strategies.

bacterial diversity↗

The contribution of bioenergy to the decarbonization of transport: a multi-model assessment

The expected growth in the demand for passenger and freight services exacerbates the challenges of reducing transport GHG emissions, especially as commercial low-carbon alternatives to petroleum fuels are limited for shipping, air and long-distance road travel. Biofuels can offer a pathway to significantly reduce emissions from these sectors, as they can easily substitute for conventional liquid fuels in internal combustion engines. In this paper, we assess the potential of bioenergy to reduce transport GHG emissions through an analysis leveraging various integrated assessment models and scenarios, as part of the 33rd Energy Modeling Forum study (EMF-33). Furthermore, we find that bioenergy can contribute a significant, albeit not dominant, proportion of energy supply to the future transport sector: in scenarios aiming to keep the temperature increase below 2 °C by the end of the twenty-first century, models project that in 2100 bioenergy can provide on average 42 EJ/yr (ranging from 5 to 85 EJ/yr) for transport (compared to 3.7 EJ in 2018), mainly through lignocellulosic fuels. This makes up 9–62% of final transport energy use. Only a small amount of bioenergy is projected to be used in transport through electricity and hydrogen pathways, with a larger role for biofuels in road passenger transport than in freight. The association of carbon capture and storage (CCS) with bioenergy technologies (BECCS) is a key determinant in the role of biofuels in transport, because of the competition for biomass feedstock to provide other final energy carriers along with carbon removal. Among models that consider CCS in the biofuel conversion process the average market share of biofuels is 21% in 2100 (ranging from 2 to 44%), compared to 10% (0–30%) for models that do not. Cumulative direct emissions from the transport sector account for half of the emission budget (from 306 to 776 out of 1,000 GtCO 2 ). However, the carbon intensity of transport decreases as much as other energy sectors in 2100 when accounting for process emissions, including carbon removal from BECCS. Lignocellulosic fuels become more attractive for transport decarbonization if BECCS is not feasible for any energy sectors. Since global transport service demand increases and biomass supply is limited, its allocation to and within the transport sector is uncertain and sensitive to assumptions about political as well as technological and socioeconomic factors.

54 ENVIRONMENTAL SCIENCES↗

Bioenergy sorghum’s deep roots: A key to sustainable biomass production on annual cropland

Abstract Bioenergy sorghum has high biomass yield potential, drought resilience, good nitrogen use efficiency, and a root system that contributes to the accumulation of soil organic carbon. In this study, field grown bioenergy sorghum root systems were analyzed during the growing season to characterize their depth, biomass, morphology, anatomy, and gene expression profiles. Bioenergy sorghum roots grew continuously during a 155‐day growing season producing ~175 nodal roots, accumulating ~7 Mg of dry biomass per hectare, and reaching >2 m deep in the soil profile. Nodal roots within 20 cm of the stem were 1–5 mm in diameter, whereas roots deeper in soil profiles were enriched in lateral roots with small diameters (~30–500 µm) enabling growth through soil macropores. In older field‐grown plants, roots with intact endodermal, vascular and inner root tissues were surrounded by degraded or aerenchyma‐filled epidermal and cortical cell layers. Transcriptome analysis of nodal, surface, and deep roots identified >2,500 differentially expressed genes involved in root growth, transport, adaptation, defense, and AMF–root interaction. Deep roots (180–240 cm) differentially expressed genes that regulate lateral root growth. Surface roots (0–20 cm) located mid‐row differentially expressed genes involved in nitrate transport, whereas ammonium transport genes were expressed in surface and deep roots and genes involved in phosphate transport were expressed in nodal, surface, and deep roots. Overall, bioenergy sorghum's long growing season enables root systems to grow deeper and accumulate more biomass than annual grain crops such as maize, attributes that could help restore annual cropland soil organic carbon levels and improve soil productivity. Deep roots active in nutrient transport are positioned to take‐up fertilizer leached deep into soil profiles mitigating potential nutrient run‐off. Bioenergy sorghum's large and deep root system is a key to sustainable production of biofuels, biopower, and bioproducts on annual cropland.

59 BASIC BIOLOGICAL SCIENCES↗

A new bioenergy model that simulates the impacts of plant‐microbial interactions, soil carbon protection, and mechanistic tillage on soil carbon cycling

Abstract Advancing our predictive understanding of bioenergy systems is critical to design decision tools that can inform which feedstock to plant, where to plant it, and how to manage its production to provide both energy and ecosystem carbon (C) benefits. Here, we lay the foundation for that advancement by integrating recent developments in the science of belowground processes in shaping the C cycle into a new bioenergy model, FUN‐BioCROP (Fixation and Uptake of Nitrogen‐Bioenergy Carbon, Rhizosphere, Organisms, and Protection). We show that FUN‐BioCROP can approximate the historical trajectory of soil C dynamics as natural ecosystems were successively converted into intensive agriculture and bioenergy systems. This ability relies in part on a novel tillage representation that mechanistically models tillage as a process that increases microbial access to C. Importantly, the impacts of tillage and feedstock choice also influence FUN‐BioCROP simulations of warming responses with no‐till perennial feedstocks, miscanthus, and switchgrass, having more C that is unprotected and susceptible to warming than tilled annual feedstocks like corn–corn–soybean. However, this susceptibility to warming is balanced by a greater potential for increases in belowground C allocation to enhance soil C stocks in perennial systems. Collectively, our model results highlight the importance of belowground processes in evaluating the ecosystem C benefits of bioenergy production.

09 BIOMASS FUELS↗

Community engagement in the development of bioenergy projects from cellulosic urban waste feedstock in Hawaii for sustainable aviation fuel

The purpose of the research project was to reveal the perceptions of residents and communities of the City and County of Honolulu concerning bioenergy projects, feedstock, and sustainable aviation fuel. The perception study was conducted via community-scale surveys, interviews, and town meetings to gather feedback on the preliminary design of a proposed bioenergy project, including feedstock choice and the need for sustainable aviation fuel in Hawaii. Residents on the west side of Oahu were targeted due to their proximity to the proposed plant site location. Findings from this study aim to identify resident perceptions, understanding, and desire for bioenergy projects and new infrastructure to, improve the energy efficiency and sustainability of Hawaiian islands. While Hawaii has created policies and mandates to move toward 100% renewable energy sources by 2045, the focus has been predominately on renewable electricity, largely overlooking other sustainable energy options such as sustainable aviation fuel. There is a lack of research on the community engagement and perceptions of Hawaiian residents on bioenergy projects and sustainable aviation fuel, contributing to the low adoption of bioenergy projects on the islands. Insights from this study aim to add literature on the need for community engagement in the design process, the importance of accepting new sustainable infrastructure, and the production and use of sustainable aviation fuels.

09 BIOMASS FUELS↗

Impact of Storage Conditions on the Quality and Viability of Switchgrass as a Bioenergy Crop

With growing energy demands and climate concerns, advancements in bioenergy have become imperative. Biofuels promote energy independence, reduce fossil fuel reliance, and cut greenhouse gas emissions. Switchgrass (Panicum virgatumis) is an ideal bioenergy crop due to its ability to thrive on marginal lands unsuitable for food crops and its drought tolerance, rendering it a low-maintenance, high-yield option. In the bioenergy industry, energy crops are typically stored to facilitate supply chain management and ensure a continuous supply despite seasonal availability. However, the effective utilization of bioenergy crops is typically contingent upon addressing the challenges associated with biomass storage. These challenges include high moisture content that promotes biological degradation of the biomass leading to increased risk of pathogenic microbes, and chemical degradation that increases the ratio of inconvertible, inorganic materials. These issues lead to a reduction of feedstock value, diminishing the biomass-to-biofuel conversion efficacy, making switchgrass and other bioenergy crops less effective as fuel sources. This project aims to improve the storage of purpose-grown energy crops. Aerobic storage trials were conducted under varying moisture contents to stimulate real-world environmental exposure. Switchgrass samples were rewetted to 30% or 35% and stored in a bioreactor for approximately one month, or until cellular respiration ceased. Degradation indicators, such as dry matter loss, temperature changes, and cellular respiration, were measured throughout this process. Samples for compositional analysis, 16S, and ITS were taken at three different time points: before, during, and after storage, to monitor changes in biomass, microbial communities, and metabolites over time. Preliminary data indicate that dry matter loss is proportional to cellular respiration, with higher moisture content (35%) leading to higher temperatures and elevated dry matter loss. Compositional analysis and microbial community analysis are in progress. This research will provide a comprehensive understanding of storage, helping to identify stability factors in energy crops and improve best management practices for biomass producers.

09 - BIOMASS FUELS↗

Empirical Evidence for the Potential Climate Benefits of Decarbonizing Light Vehicle Transport in the U.S. with Bioenergy from Purpose-Grown Biomass with and without BECCS

Climate mitigation scenarios limiting global temperature increases to 1.5 °C rely on decarbonizing vehicle transport with bioenergy production plus carbon capture and storage (BECCS), but climate impacts for producing different bioenergy feedstocks have not been directly compared experimentally or for ethanol vs electric light-duty vehicles. A field experiment at two Midwest U.S. sites on contrasting soils revealed that feedstock yields of seven potential bioenergy cropping systems varied substantially within sites but little between. Bioenergy produced per hectare reflected yields: miscanthus > poplar > switchgrass > native grasses ≈ maize stover (residue) > restored prairie ≈ early successional. Greenhouse gas emission intensities for ethanol vehicles ranged from 20 to -179 g CO 2 e MJ –1 : maize stover $\gg$ miscanthus ≈ switchgrass ≈ native grasses ≈ poplar > early successional ≥ restored prairie; direct climate benefits ranged from ~80% (stover) to 290% (restored prairie) reductions in CO 2 e compared to petroleum and were similar for electric vehicles. With carbon capture and storage (CCS), reductions in emission intensities ranged from 204% (stover) to 416% (restored prairie) for ethanol vehicles and from 329 to 558% for electric vehicles, declining 27 and 15%, respectively, once soil carbon equilibrates within several decades of establishment. Extrapolation based on expected U.S. transportation energy use suggests that, once CCS potential is maximized with CO 2 pipeline infrastructure, negative emissions from bioenergy with CCS for light-duty electric vehicles could capture >900 Tg CO 2 e year –1 in the U.S. In the future, as other renewable electricity sources become more important, electricity production from biomass would offset less fossil fuel electricity, and the advantage of electric over ethanol vehicles would decrease proportionately.

54 ENVIRONMENTAL SCIENCES↗

Accelerating the development of a sustainable bioenergy portfolio through stable isotopes

Bioenergy could help limit global warming to 2°C above pre-industrial levels while supplying almost a fourth of the world's renewable energy needs by 2050. However, the deployment of bioenergy raises concerns that adoption at meaningful scales may lead to unintended negative environmental consequences. Meanwhile, the full consolidation of a bioenergy industry is currently challenged by a sufficient, resilient, and resource-efficient biomass supply and an effective conversion process. Here, we provide a comprehensive analysis of how stable isotope approaches have accelerated the development of a robust bioeconomy by advancing knowledge about environmental sustainability, feedstock development, and biological conversion. We show that advances in stable isotope research have generated crucial information to (1) gain mechanistic insight into the potential of bioenergy crops to mitigate climate change as well as their impact on water and nutrient cycling; (2) develop high-yielding, resilient feedstocks that produce high-value bioproducts in planta; and (3) engineer microbes to enhance feedstock conversion to bioenergy products. Further, we highlight knowledge gaps that could benefit from future research facilitated by stable isotope approaches. We conclude that advances in mechanistic knowledge and innovations within the field of stable isotopes in cross-disciplinary research actions will greatly contribute to breaking down the barriers to establishing a robust bioeconomy.

59 BASIC BIOLOGICAL SCIENCES↗

Data for "Field-scale Evaluation of Ecosystem Service Benefits of Bioenergy Switchgrass"

Purpose-grown perennial herbaceous species are nonfood crops specifically cultivated for bioenergy production and have the potential to secure bioenergy feedstock resources while enhancing ecosystem services. This study assessed soil greenhouse gas emissions (CO2 and N2O), nitrate (NO3-N) leaching reduction potential, evapotranspiration (ET), and water-use efficiency (WUE) of bioenergy switchgrass ( Panicum virgatum L.) in comparison to corn ( Zea mays L.). The study was conducted on field-scale plots in Urbana, IL, during the 2020–2022 growing seasons. Switchgrass was established in 2020 and urea-fertilized at 56 kg N ha−1 year−1. Corn management followed best management practices for the US Midwest, including no-till and 202 kg N ha−1 year−1 fertilization, applied as urea–ammonium nitrate (32%). Our results showed lower direct N2O emissions in switchgrass compared to corn. Although soil CO2 emissions did not differ significantly during the establishment year, emissions in subsequent years were over 50% higher in switchgrass than in corn, likely due to increased belowground biomass, which was over five times higher in switchgrass. Nitrate-N leaching decreased as the switchgrass stand matured, reaching 80% lower than in corn by the third year. Differences in ET and WUE between corn and switchgrass were not significant; however, results indicate a trend toward reduced WUE in switchgrass under drought, driven by lower aboveground biomass production. Our study demonstrates that switchgrass can be implemented at a commercial scale without negatively impacting the hydrological cycle, while potentially reducing N losses through nitrate-N leaching and soil N2O emissions, and enhancing belowground C storage.

field data↗

Carbon mitigation payments can reduce the riskiness of bioenergy crop production

Abstract Perennial bioenergy crops provide substantial carbon mitigation benefits but have risky returns. We couple economic analysis with a biogeochemical model (DayCent) to examine the effect of carbon mitigation payments on the spatially varying bioenergy crop returns and risk profiles relative to conventional crops across the rainfed United States. These payments increase the likelihood of positive profit in the Midwest for miscanthus and southern states for switchgrass. At low biomass prices, these payments make bioenergy crops appealing to risk‐averse farmers. At moderate biomass prices, these payments make bioenergy crops appealing to all farmers regardless of risk preference.

09 BIOMASS FUELS↗