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The BioEnergy Science Center, led by Oak Ridge National Laboratory, has been making advances in biofuels for over a decade. These achievements in plant genomics, microbial engineering, biochemistry, and plant physiology will carry over into the Center for Bioenergy Innovation, a new Department of Energy bioenergy research center.
Over the past 7 years, the US Department of Energy's Office of Biological and Environmental Research has funded three Bioenergy Research Centers (BRCs). These centers have developed complementary and collaborative research portfolios that address the key technical and economic challenges in biofuel production from lignocellulosic biomass. All three centers have established a close, productive relationship with DOE's Joint Genome Institute (JGI). This special issue of Bioenergy Research samples the breadth of basic science and engineering work required to underpin a diverse, sustainable, and robust biofuel industry. In this report, which was collaboratively produced by all three BRCs, we discuss the BRC contributions over their first 7 years to the development of renewable transportation fuels. In additon, we also highlight the BRC research published in the current issue and discuss technical challenges in light of recent progress.
This study investigates potential economic and groundwater driven transitions from irrigated maize production—the dominant irrigated cropping system in the High Plains Aquifer (HPA) region—to alternative crops such as sorghum and switchgrass, two common bioenergy feedstocks. Unsustainable groundwater extraction in the U.S. High Plains presents critical challenges including reduced irrigation capacities, diminished crop yields, lower land values, and escalating energy costs. Using a spatially explicit optimization framework combined with comprehensive economic and hydrogeological data, we evaluate optimal land-use strategies and irrigation system investments over a 30-year planning period. Results indicate significant regional variability in the future economic viability of irrigated agriculture, driven by differences in aquifer recharge rates, groundwater availability, and market conditions. Nebraska and parts of northern Texas can sustain irrigated maize profitability due to relatively favorable groundwater conditions and lower land rents, respectively. In contrast, many portions of Kansas and southern Texas are more likely to transition to dryland agriculture within two decades. Colorado and New Mexico show potential for significant adoption of switchgrass production as an alternative biomass-based energy crop. Overall, over the 30-year horizon, our model implies that approximately 23% of currently irrigated maize area across the HPA region may transition to dryland farming under business-as-usual conditions. This transition is complemented by a threefold increase in non-irrigated sorghum production, from 0.20 to 0.77 Mt yr−1, indicating that groundwater-driven shifts in agricultural production may support a larger regional base for bioenergy feedstocks. The study also reveals opportunities for producers to optimize economic returns and biomass production potential.
Advances in engineering of bioenergy crops were driven over the past years by adapting technological breakthroughs and accelerating conventional applications but also exposed intriguing challenges. New tools revealed rich interconnectivity in the exponentially growing and dynamic 'big' omics data' of metabolomes, transcriptomes, and genomes at previously inaccessible magnitude (global, cross-species, meta-) and resolution (single cell). Insights enabled fresh hypotheses and stimulated disciplines such as functional genomics with discovery of broad regulatory networks and their determinants, that is, DNA parts, including promoters, regulatory elements, and transcription factors. Their rational design, assembly into increasingly complex blueprints, and installation into diverse chassis is an existing frontier that may benefit from emerging technologies to address bottlenecks. Interweaving nature-inspired to fully synthetic parts has already allowed building of fine-tuned regulatory circuits, or new-to-nature metabolic routes insulated from the biological context of the chassis species. Similarly, developments and the evolving need for unifying principles in plant transformation and species-agnostic technologies highlight future opportunities for engineering the next generation of bioenergy plants.
Data sets for material included in "A 13-year record indicates differences in the duration and depth of soil carbon accrual among potential bioenergy crops" by Kantola et al., 2025, in Global Change Biology Bioenergy. Data include soil organic carbon (SOC), carbon stable isotope ratios, annual belowground biomass, and annual post-harvest litter for four crops, maize/soybean, miscanthus, switchgrass, and prairie, between 2008 and 2021.
Stem internodes of bioenergy sorghum inbred R.07020 are longer at high plant density (shade) than at low plant density (control). Initially, the youngest newly-formed subapical stem internodes of shade-treated and control plants are comparable in length. However, full-length internodes of shade-treated plants are three times longer than the internodes of the control plants. To identify the early molecular events associated with internode elongation in response to shade, we analyzed the transcriptome of the newly-formed internodes of shade-treated and control plants sampled between 4 and 6 hr after the start of the light period (14 hr light/10 hr dark). Sorghum genes homologous to the Arabidopsis shade marker genes ATHB2 and PIL1 were not differentially expressed. The results indicate that shade signals promote internode elongation indirectly because sorghum internodes are not illuminated and grow while enclosed with leaf sheaths. Sorghum genes homologous to the Arabidopsis morning-phased circadian clock genes LHY, RVE, and LNK were downregulated and evening-phased genes such as TOC1, PRR5, and GI were upregulated in young internodes in response to shade. We hypothesize that a change in the function or patterns of expression of the circadian clock genes is the earliest molecular event associated with internode elongation in response to shade in bioenergy sorghum. Increased expression of CycD1, which promotes cell division, and decreased expression of cell wall-loosening and MBF1-like genes, which promote cell expansion, suggest that shade signals promote internode elongation in bioenergy sorghum in part through increasing cell number by delaying transition from cell division to cell expansion.
The use of fossil fuels is the primary source of greenhouse gas emissions but there are alternatives to these especially in the form of biofuels, fuels derived from bioenergy crops. This paper aims to determine farmers’ potential adoption rates of newly introduced bioenergy crops with a specific example of carinata in the state of Georgia. The determination is done using an agent-based modeling technique with two principal assumptions—farmers are profit maximizer and they are influenced by neighboring farmers. Two diffusion parameters (traditional and expansion) are followed along with two willingness (high and low) scenarios to switch at varying production economics to carinata and other prominent traditional field crops (cotton, peanuts, corn) in the study region. We find that a contract prices around $9, $8 and $7 can be a viable option for encouraging farmers to adopt carinata in low, average, and high profit conditions, respectively. Expansion diffusion (that diffuses all over the geographical area), rather than centered to the few places like traditional diffusion at the early stage of adoption in conjunction with higher willingness conditions influences higher adoption rates in the short-term. As such, the model can be used to understand the behavioral economics of carinata in Georgia and beyond, as well as offering a potential tool to study similar bioenergy crops.
This study is a model comparison assessing the drivers and impacts of bioenergy production on the global land system and the interaction with other land use based mitigation options in the context of the EMF 27 project. We compare and evaluate results from three integrated assessment models (GCAM, IMAGE, and ReMIND/MAgPIE). All three models project that dedicated bioenergy crops and biomass residues are a potentially important and cost-effective component of the energy system. But bioenergy deployment levels and feedstock composition vary notably across models as do the implications for land-use and greenhouse gas emissions and the interaction with other land use based mitigation measures. Despite numerous model differences, we identify a few that are likely contributing to differences in land-use and emissions attributable to energy crop deployment.
Biomass deconstruction is a crucial step in the production of lignocellulosic biofuels and bioproducts. However, identifying and selecting an optimal pretreatment solvent that enhances enzymatic saccharification while being cost-efficient and ensuring sustainability remains a challenge. In this study, we compare the effectiveness of the biocompatible ionic liquid cholinium lysinate ([Ch][Lys]) against the distillable solvent ethanolamine, when used for the pretreatment of mixed bioenergy feedstocks, including poplar, switchgrass, and sorghum. [Ch][Lys] was used at a concentration of 10 % wt. in a one-pot configuration without biomass washing and ethanolamine was used in a concentrated form and removed with a vacuum oven, before performing enzymatic hydrolysis and microbial conversion. Our results show that ethanolamine pretreatment consistently enhances the glucose yield across various biomass types compared to [Ch][Lys], with improvements ranging from 22.0 % to 52.7 %. The highest combined sugar release was observed when the three feedstocks were combined in equal amounts and pretreated with ethanolamine, achieving a glucose yield of 84.6 % and a xylose yield of 76.6 %. Additionally, ethanolamine exhibited exceptional solvent recovery efficiency, with removal efficiencies exceeding 99.8 % at 120 °C across all feedstocks, highlighting its advantage over non-distillable solvents. While both solvents produced biocompatible hydrolysates, the hydrolysates prepared using ethanolamine resulted in higher bioproduct formation. These findings highlight the industrial relevance of selecting recyclable and biocompatible solvents for scalable, sustainable, and cost-effective bioenergy production. This study contributes to the development of economically viable and scalable pretreatment technologies for bioenergy applications using different feedstocks and process configurations.
Switchgrass is a promising bioenergy feedstock due to its high biomass yield potential, adaptability to marginal lands, and low carbon intensity for feedstock production. However, accurate cost estimation and assessment of greenhouse gas (GHG) emissions for the energy-intensive harvesting process are essential for evaluating the sustainability of bioenergy. This study provides a comparative analysis of two harvesting methods: the Stepwise Method, which separates operations into multiple stages, and the Integrated Method, which combines mowing and raking into a single pass. The analysis was conducted under four scenarios based on field sizes and biomass yields. Using three years of field-scale switchgrass harvest data from 125 sites, GHG emissions, energy consumption, and harvesting costs were quantified using the GREET model and techno-economic analysis. Additionally, regression analysis identified key climate and operational factors affecting fuel consumption. The Stepwise method was the most cost-effective for large fields with high biomass yield, achieving the lowest harvesting costs ($37.70 per ton). In contrast, the Integrated Method performed better in small fields and low-yield conditions, reducing GHG emissions by 9 % and energy use by 5 %. Regression analysis confirmed that a larger field size reduced fuel consumption, while higher biomass yield and longer operational time increased fuel use. Maximum temperature also contributed to a slight increase in fuel consumption. Furthermore, these results provide actionable insights for optimizing harvesting strategies based on field-specific conditions and operational goals, contributing to the economic and environmental sustainability of bioenergy production.
Innovative bioenergy projects show a growing diversity in biomass pathways, transformation technologies and end-products, leading to complex new processes. Existing energy-based indicators are not designed to include multiple impacts and are too constrained to assess the sustainability of these processes. Alternatively, indicators based on exergy, a measure of “qualitative energy”, could allow a more holistic view. Exergy is increasingly applied in analyses of both technical and biological processes. But sustainability assessments including exergy calculations, are not very common and are not generally applicable to all types of impact. Hence it is important to frame the use of exergy for inclusion in a sustainability assessment. This paper reviews the potentials and the limitations of exergy calculations, and presents solutions for coherent aggregation with other metrics. The resulting approach is illustrated in a case study. Within the context of sustainability assessment of bioenergy, exergy is a suitable metric for the impacts that require an ecocentric interpretation, and it allows aggregation on a physical basis. The use of exergy is limited to a measurement of material and energy exchanges with the sun, biosphere and lithosphere. Exchanges involving services or human choices are to be measured in different metrics. This combination provides a more inclusive and objective sustainability assessment, especially compared to standard energy- or carbon-based indicators. Future applications of this approach in different situations are required to clarify the potential of exergy-based indicators in a sustainability context. -- Highlights: • Innovative bioenergy projects require more advanced sustainability assessments to incorporate all environmental impacts. • Exergy-based indicators provide solutions for objective and robust measurements. • The use of exergy in a sustainability assessment is limited to material exchanges, excluding exchanges with society. • The combination of exergy-based indicators with other indicators is very appropriate. • But this is only rarely applied.
The use of life cycle assessment (LCA) as a sustainability assessment tool for agro-bioenergy system usually has an industrial agriculture bias. Furthermore, LCA generally has often been criticized for being a decision maker tool which may not consider decision takers perceptions. They are lacking in spatial and temporal depth, and unable to assess sufficiently some environmental impact categories such as biodiversity, land use etc. and most economic and social impact categories, e.g. food security, water security, energy security. This study explored tools, methodologies and frameworks that can be deployed individually, as well as in combination with each other for bridging these methodological gaps in application to agro-bioenergy systems. Integrating agronomic options, e.g. alternative farm power, tillage, seed sowing options, fertilizer, pesticide, irrigation into the boundaries of LCAs for agro-bioenergy systems will not only provide an alternative agro-ecological perspective to previous LCAs, but will also lead to the derivation of indicators for assessment of some social and economic impact categories. Deploying life cycle thinking approaches such as energy return on energy invested-EROEI, human appropriation of net primary production-HANPP, net greenhouse gas or carbon balance-NCB, water footprint individually and in combination with each other will also lead to further derivation of indicators suitable for assessing relevant environmental, social and economic impact categories. Also, applying spatio-temporal simulation models has a potential for improving the spatial and temporal depths of LCA analysis.
We present that bioenergy can be a promising solution to the energy, food and environment trilemma in China. Currently this coal-dependent nation is in urgent need of alternative fuels to secure its future energy and improve the environment. Biofuels derived from crop residues and bioenergy crops emerge as a great addition to renewable energy in China without compromising food production. This paper reviews bioenergy resources from existing conventional crop (e.g., corn, wheat and rice) residues and energy crops (e.g., Miscanthus) produced on marginal lands. The impacts of biofuel production on ecosystem services are also discussed in the context of biofuel's life cycle. It is estimated that about 280 million metric tons (Mt) of crop residue-based biomass (or 65 Mt of ethanol) and over 150 Mt of energy crop-based ethanol can become available each year, which far exceeds current national fuel ethanol production (<2 Mt year -1 ) and the 2020 national target of 10 Mt year -1 . Review on environmental impacts suggested that substituting fossil fuels with biofuels could significantly reduce greenhouse gas emissions and air pollution (e.g., particulate matter). However, the impacts of biofuel production on biodiversity, water quantity and quality vary greatly among biomass types, land sources and management practices. Improved agricultural management and landscape planning can be beneficial to ecosystem services. Lastly, a national investigation is desirable in China to inventory technical and economic potential of biomass feedstocks and evaluate the impacts of biofuel production on ecosystem services and the environment.
Perennial bioenergy crops are increasingly important for the production of ethanol and other renewable fuels, and as part of an agricultural system that alters the climate through its impact on biogeophysical and biogeochemical properties of the terrestrial ecosystem. Few earth system models (ESMs) represent such crops, however. In this study, we expand the Energy Exascale Earth System Model (E3SM) Land Model (ELMv2) to include perennial bioenergy crops with a high potential for mitigating climate change. We focus on high-productivity miscanthus and switchgrass, estimating various parameters associated with their different growth stages and performing a global sensitivity analysis to identify and optimize these parameters. The sensitivity analysis identifies five parameters associated with phenology, carbon/nitrogen allocation, stomatal conductance, and maintenance respiration as the most sensitive parameters for carbon and energy fluxes. We calibrated and validated the model against observations and found that the model closely captures the observed seasonality and the magnitude of carbon fluxes. The validated model represents the latent heat flux fairly well, but sensible heat flux for miscanthus is not well captured. Finally, we validated the model against observed leaf area index (LAI) and harvest amount and found modeled LAI captured observed seasonality , although the model underestimates LAI and harvest amount. This work provides a foundation for future ESM analyses of the interactions between perennial bioenergy crops and carbon, water, and energy dynamics in the larger earth system, and sets the stage for studying the impact of future biofuel expansion on climate and terrestrial systems.
Abstract The stems of bioenergy sorghum hybrids at harvest are > 4 m long, contain > 40 internodes and account for ~ 80% of harvested biomass. In this study, bioenergy sorghum hybrids were grown at four planting densities (~ 20,000 to 132,000 plants/ha) under field conditions for 60 days to investigate the impact shading has on stem growth and biomass accumulation. Increased planting density induced a > 2-fold increase in sorghum internode length and a ~ 22% decrease in stem diameter, a typical shade avoidance response. Shade-induced internode elongation was due to an increase in cell length and number of cells spanning the length of internodes. SbGA3ox2 (Sobic.003G045900), a gene encoding the last step in GA biosynthesis, was expressed ~ 20-fold higher in leaf collar tissue of developing phytomers in plants grown at high vs. low density. Application of GA3 to bioenergy sorghum increased plant height, stem internode length, cell length and the number of cells spanning internodes. Prior research showed that sorghum plants lacking phytochrome B, a key photoreceptor involved in shade signaling, accumulated more GA1 and displayed shade avoidance phenotypes. These results are consistent with the hypothesis that increasing planting density induces expression of GA3-oxidase in leaf collar tissue, increasing synthesis of GA that stimulates internode elongation.
Abstract We find spatial dependence in landowners’ stated intentions to make land available for bioenergy crops. Our data are generated from a contingent valuation survey of 599 owners of marginal land in southern Michigan. Employing a Bayesian framework and using these spatially explicit data, we estimate and compare non‐spatial probit and spatial Durbin probit models to examine the presence of spatial dependence in land rental intentions. Results show that intentions to rent land for bioenergy crop production are spatially dependent. This spatial dependence arises both from the land supply intentions of nearby landowners and from spatial spillover effects of landowner characteristics and attitudes towards environmental amenities and the disamenities of land rental. We show that ignoring spatial dependence in the intentions of neighbouring landowners to participate in land rental markets for bioenergy feedstocks can lead to distortions that underestimate total effects. Our finding implies that studies of land use and crop supply should test for spatial interactions in order to make accurate inferences.
Across energy, agricultural and forestry landscapes, the production of biomass for energy has emerged as a controversial driver of land-use change. We present a novel, simple methodology, to probe the potential global sustainability limits of bioenergy over time for energy provision and climate change mitigation using a complex-systems approach for assessing land-use dynamics. Primary biomass that could provide between 70 EJ year -1 and 360 EJ year -1 , globally, by 2050 was simulated in the context of different land-use futures, food diet patterns and climate change mitigation efforts. Our simulations also show ranges of potential greenhouse gas emissions for agriculture, forestry and other land uses by 2050, including not only above-ground biomass-related emissions, but also from changes in soil carbon, from as high as 24 GtCO 2 eq year-1 to as low as minus 21 GtCO 2 eq year -1 , which would represent a significant source of negative emissions. Based on the modelling simulations, the discussions offer novel insights about bioenergy as part of a broader integrated system. As a result, there are sustainability limits to the scale of bioenergy provision, they are dynamic over time, being responsive to land management options deployed worldwide.
While renewable biofuels can reduce negative effects of fossil fuel energy consumption, the magnitude of their benefits depends on the magnitude of N 2 O emissions. High variability of N 2 O emissions overpowers efforts to curb uncertainties in estimating N 2 O fluxes from biofuel systems. In this study, we explored (a) N 2 O production via bacterial denitrification and (b) N 2 O emissions from soils under several contrasting bioenergy cropping systems, with specific focus on explaining N 2 O variations by accounting for soil pore characteristics. Intact soil samples were collected after 9 years of implementing five biofuel systems: continuous corn with and without winter cover crop, monoculture switchgrass, poplars, and early–successional vegetation. After incubation, N 2 O emissions were measured and bacterial denitrification was determined based on the site–preference method. Soil pore characteristics were quantified using X–ray computed microtomography. Three bioenergy systems with low plant diversity, that is, corn and switchgrass systems, had low porosities, low organic carbon contents, and large volumes of poorly aerated soil. In these systems, greater volumes of poorly aerated soil were associated with greater bacterial denitrification, which in turn was associated with greater N 2 O emissions ( R 2 = 0.52, p < 0.05). However, the two systems with high plant diversity, that is, poplars and early–successional vegetation, over the 9 years of implementation had developed higher porosities and organic carbon contents. In these systems, volumes of poorly aerated soil were positively associated with N 2 O emissions without a concomitant increase in bacterial denitrification. Our results suggest that changes in soil pore architecture generated by long–term implementation of contrasting bioenergy systems may affect the pathways of N 2 O production, thus, change associations between N 2 O emissions and other soil properties. In conclusion, plant diversity appears as one of the factors determining which microscale soil characteristics will influence the amounts of N 2 O emitted into the atmosphere and, thus, which can be used as effective empirical predictors.