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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Modeling spatial dependence and economic hotspots in landowners’ willingness to supply bioenergy crops in the northeastern United States

This paper investigates the spatial heterogeneity of landowners’ willingness to supply three bioenergy crops: switchgrass, Miscanthus , and willow, in the northeastern United States. Spatial heterogeneity might arise for several reasons. For example, landowners closer to bioenergy processing plants might be more likely to be willing to supply bioenergy crops, and landowners who are more willing to supply bioenergy crops may be spatially clustered because they share similar land attributes, demographics, experiences, and/or values. Using high–resolution GIS data related to the location of pellet plants utilizing bioenergy crops and survey data related to landowners’ characteristics including spatial location, we estimate a spatial probit model to explain the variation in individual–specific reservation prices (RPs)—the feedstock price at which landowners become willing to supply a bioenergy crop. We find that respondents’ RP is lower the closer they live to their nearest pellet plant and spatial dependency is only present for switchgrass supply. We also identify three economic hotspots (areas with high potential supply and low RPs) for each bioenergy crop. We believe that bioenergy supply chains could be developed around these hotspots.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Quantifying Climate Change Effects of Bioenergy and BECCS: Critical Considerations and Guidance on Methodology

Bioenergy is a critical element in many national and international climate change mitigation efforts, including as a carbon dioxide removal strategy combined with the capture and durable geological storage of flue gas emissions (BECCS). However, divergent results on the effectiveness of bioenergy as a climate change mitigation measure are reported in the scientific literature. Climate impacts of bioenergy depend on case-specific factors, primarily biophysical features of the biomass production system, and the design and efficiency of conversion and capture processes. Estimates of climate impacts are also strongly affected by methodological choices and assumptions, and much of the divergence between studies derives from differences in the assumed alternate use of the land or feedstock, the alternate energy source and the system boundaries applied. We present a methodology to support robust estimates of the climate change effects of bioenergy systems, updating the standard methodology developed by the International Energy Agency's Technology Collaboration Program on Bioenergy. We provide guidance on the key choices including the reference land use and energy system that bioenergy is assumed to displace, spatial and temporal system boundaries, co-product handling, climate forcers considered, metrics applied and time horizon of impact assessment. Researchers should consider the whole bioenergy system including all life cycle stages, and choose system boundaries, reference systems and treatment of co-products that are consistent with the intended application of the results. The assessment should be normalised to a functional unit that can be compared with other systems delivering an equivalent quantity of the same function. All significant climate forcers should be included, and climate effects should be quantified using appropriate impact assessment methods that distinguish the impact of time. Consistency in methodology and interpretation will facilitate comparison between studies of different bioenergy systems.

09 BIOMASS FUELS↗
DOE OSTI2014

Bioenergy in Energy Transformation and Climate Management

Unlike fossil fuels, biomass is a renewable resource that can sequester carbon during growth, be converted to energy, and then re-grown. Biomass is also a flexible fuel that can service many end-uses. This paper explores the importance of bioenergy to potential future energy transformation and climate change management. Using a model comparison of fifteen models, we characterize and analyze future dependence on, and the value of, bioenergy in achieving potential long-run climate objectives—reducing radiative forcing to 3.7 and 2.8 W/m2 in 2100 (approximately 550 and 450 ppm carbon dioxide equivalent atmospheric concentrations). Model scenarios project, by 2050, bioenergy growth of 2 to 10% per annum reaching 5 to 35 percent of global primary energy, and by 2100, bioenergy becoming 15 to 50 percent of global primary energy. Non-OECD regions are projected to be the dominant suppliers of biomass, as well as consumers, with up to 35 percent of regional electricity from biopower by 2050, and up to 70 percent of regional liquid fuels from biofuels by 2050. Bioenergy is found to be valuable to many models with significant implications for mitigation costs and world consumption. The availability of bioenergy, in particular biomass with carbon dioxide capture and storage (BECCS), notably affects the cost-effective global emissions trajectory for climate management by accommodating prolonged near-term use of fossil fuels. We also find that models cost-effectively trade-off land carbon and nitrous oxide emissions for the long-run climate change management benefits of bioenergy. Overall, further evaluation of the viability of global large-scale bioenergy is merited.

Rose, Steven K.↗
DOE OSTI2024

A Novel Framework to Evaluate the Costs and Potential of Bioenergy in Decarbonization of the U.S. Economy

The long-term strategy of the United States targets reaching economy-wide net-zero emissions by 2050 and a carbon-neutral electricity grid by 2035 (U.S. Department of State and U.S. Executive Office of the President, 2021). Meeting these targets would require considerable changes to the energy system. Some key characteristics of illustrative net-zero energy systems include increased penetration of renewable energy and carbon sources, use of CO2 capture and storage (CCS) in hard-to-abate sectors, and a greater role for energy carriers such as electricity and hydrogen (Davis et al, 2018). Another common feature of such energy systems is the need for carbon dioxide removal (CDR) approaches (Horowitz et al, 2022). Across all these characteristics of net-zero energy systems, bioenergy and biomass feedstock is anticipated to play an important role. Biomass feedstock serves as a renewable carbon source. This can enable conversion of such feedstock into fuels and energy carriers for hard-to-abate sectors such as aviation. Indeed, the U.S. Government has a target to meet all jet fuel demand by 2050 from sustainable aviation fuel (SAF), where biofuel pathways are likely to have an important role (EERE, 2020). Bioenergy is also highly versatile with the possibility to convert feedstock into electricity, hydrogen, liquid fuels, heat or high-value products, based on biomass type, demand and technology availability (Clarke et al, 2022). Combination of bioenergy with CCS can also nominally deliver CDR (Fuhrman et al, 2023). As such, the share of bioenergy is expected to grow by at least five time across scenarios studied for the long-term strategy of the U.S. between 2020 and 2050 (Horowitz et al, 2022). Notwithstanding the role of bioenergy in the energy systems, its deployment, costs and scalability are influenced by a number of factors. Some of these factors pertain to policy interventions such as imposition of a binding decarbonization target either at an economy-wide level or the sectoral level. Resource availability and type of biomass feedstock also varies considerably across regions. From a technological perspective, the readiness of bioenergy conversion pathways is subject to high variability. This influences the costs of deployment. Moreover, the sourcing of feedstock, grid carbon intensity, and co-product handling approaches all affect the life cycle efficacy of bioenergy. The latter, in turn, is particularly important in determining the extent to which bioenergy with CCS or BECCS can effectively deliver CDR (Fajardy and Mac Dowell, 2017).

air emission↗
DOE OSTI2023

Estimating Field-Level Perennial Bioenergy Grass Biomass Yields Using the Normalized Difference Red-Edge Index and Linear Regression Analysis for Central Virginia, USA

We investigated the indicative power of the normalized difference red-edge index (NDRE) for estimating field-level perennial bioenergy grass biomass yields utilizing Sentinel-2 imagery and a linear regression model as a rapid, cost-effective method for biomass yield estimations for bioenergy. We used 2019 data from three study sites containing mature perennial bioenergy grass stands in central Virginia, USA. Of the simulated daily NDRE values based on the temporally weighted averaging of two temporal neighbors, we found the strongest index–yield correlation on 11 August (R = 0.85). We estimated the perennial bioenergy grass biomass yields for (1) all sites using the data pooled from the three sites (all-site estimation) and (2) each site using the data pooled from the other two sites (cross-site estimation). The estimated field-level perennial bioenergy grass biomass yields strongly correlated with the recorded yields (average R2 = 0.76), with a root mean square error (RMSE) of 1.5 Mg/ha and a mean absolute error (MAE) of 1.2 Mg/ha for the all-site estimation. For the cross-site estimation, the site with diverse perennial grass types had the weakest correlation (R2 = 0.44) of the sites, indicating a difficulty in accounting for heterogeneous index–yield relationships in a single model. In addition to identifying a strong indicative power of the NDRE for estimating the overall perennial bioenergy grass biomass yields at a field level, the findings from this study call for an analysis across multiple perennial grasses and a comparison using multiple sites to understand (1) if the indicative power of the index shifts from the biomass of the specific perennial bioenergy grass type to the overall biomass during the growing season and (2) the level of perennial bioenergy grass heterogeneity that may hinder the remotely sensed biomass yield estimation using a single model.

09 BIOMASS FUELS↗
DOE OSTI2014

Land-use legacies regulate decomposition dynamics following bioenergy crop conversion

Land-use conversion into bioenergy crop production can alter litter decomposition processes tightly coupled to soil carbon and nutrient dynamics. Yet, litter decomposition has been poorly described in bioenergy production systems, especially following land-use conversion. Predicting decomposition dynamics in postconversion bioenergy production systems is challenging because of the combined influence of land-use legacies with current management and litter quality. To evaluate how land-use legacies interact with current bioenergy crop management to influence litter decomposition in different litter types, we conducted a landscape-scale litterbag decomposition experiment. We proposed land-use legacies regulate decomposition, but their effects are weakened under higher quality litter and when current land use intensifies ecosystem disturbance relative to prior land use. We compared sites left in historical land uses of either agriculture (AG) or Conservation Reserve Program grassland (CRP) to those that were converted to corn or switchgrass bioenergy crop production. Enzyme activities, mass loss, microbial biomass, and changes in litter chemistry were monitored in corn stover and switchgrass litter over 485 days, accompanied by similar soil measurements. Across all measured variables, legacy had the strongest effect (P < 0.05) relative to litter type and current management, where CRP sites maintained higher soil and litter enzyme activities and microbial biomass relative to AG sites. Decomposition responses to conversion depended on legacy but also current management and litter type. Within the CRP sites, conversion into corn increased litter enzymes, microbial biomass, and litter protein and lipid abundances, especially on decomposing corn litter, relative to nonconverted CRP. However, conversion into switchgrass from CRP, a moderate disturbance, often had no effect on switchgrass litter decomposition parameters. Thus, legacies shape the direction and magnitude of decomposition responses to bioenergy crop conversion and therefore should be considered a key influence on litter and soil C cycling under bioenergy crop management.

09 BIOMASS FUELS↗
DOE OSTI2016

Watershed‐scale impacts of bioenergy crops on hydrology and water quality using improved SWAT model

Abstract Cellulosic bioenergy feedstock such as perennial grasses and crop residues are expected to play a significant role in meeting US biofuel production targets. We used an improved version of the Soil and Water Assessment Tool ( SWAT ) to forecast impacts on watershed hydrology and water quality by implementing an array of plausible land‐use changes associated with commercial bioenergy crop production for two watersheds in the Midwest USA . Watershed‐scale impacts were estimated for 13 bioenergy crop production scenarios, including: production of Miscanthus × giganteus and upland Shawnee switchgrass on highly erodible landscape positions, agricultural marginal land areas and pastures, removal of corn stover and combinations of these options. Water quality, measured as erosion and sediment loading, was forecasted to improve compared to baseline when perennial grasses were used for bioenergy production, but not with stover removal scenarios. Erosion reduction with perennial energy crop production scenarios ranged between 0.2% and 59%. Stream flow at the watershed outlet was reduced between 0 and 8% across these bioenergy crop production scenarios compared to baseline across the study watersheds. Results indicate that bioenergy production scenarios that incorporate perennial grasses reduced the nonpoint source pollutant load at the watershed outlet compared to the baseline conditions (0–20% for nitrate‐nitrogen and 3–56% for mineral phosphorus); however, the reduction rates were specific to site characteristics and management practices.

09 BIOMASS FUELS↗
DOE OSTI2022

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↗
DOE OSTI2025

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↗
DOE OSTI2024

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↗
DOE OSTI2021

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↗
DOE OSTI2016

Reconciling food security and bioenergy: priorities for action

Abstract Understanding the complex interactions among food security, bioenergy sustainability, and resource management requires a focus on specific contextual problems and opportunities. The United Nations’ 2030 Sustainable Development Goals place a high priority on food and energy security; bioenergy plays an important role in achieving both goals. Effective food security programs begin by clearly defining the problem and asking, ‘What can be done to assist people at high risk?’ Simplistic global analyses, headlines, and cartoons that blame biofuels for food insecurity may reflect good intentions but mislead the public and policymakers because they obscure the main drivers of local food insecurity and ignore opportunities for bioenergy to contribute to solutions. Applying sustainability guidelines to bioenergy will help achieve near‐ and long‐term goals to eradicate hunger. Priorities for achieving successful synergies between bioenergy and food security include the following: (1) clarifying communications with clear and consistent terms, (2) recognizing that food and bioenergy need not compete for land and, instead, should be integrated to improve resource management, (3) investing in technology, rural extension, and innovations to build capacity and infrastructure, (4) promoting stable prices that incentivize local production, (5) adopting flex crops that can provide food along with other products and services to society, and (6) engaging stakeholders to identify and assess specific opportunities for biofuels to improve food security. Systematic monitoring and analysis to support adaptive management and continual improvement are essential elements to build synergies and help society equitably meet growing demands for both food and energy.

09 BIOMASS FUELS↗
DOE OSTI2021

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↗
DOE OSTI2017

2015 Bioenergy Market Report

This report is an update to the 2013 report and provides a status of the markets and technology development involved in growing a domestic bioenergy economy as it existed at the end of 2015. It compiles and integrates information to provide a snapshot of the current state and historical trends influencing the development of bioenergy markets. This version features details on the two major bioenergy markets: biofuels and biopower and an overview of bioproducts that enable bioenergy production. The information is intended for policy-makers as well as technology developers and investors tracking bioenergy developments. It also highlights some of the key energy and regulatory drivers of bioenergy markets.

09 BIOMASS FUELS↗
DOE OSTI2024

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↗
DOE OSTI2017

Introducing perennial biomass crops into agricultural landscapes to address water quality challenges and provide other environmental services: Integrating perennial bioenergy crops into agricultural landscapes

The world is faced with a difficult multiple challenge of meeting nutritional, energy, and other basic needs, under a limited land and water budget, of between 9 and 10 billion people in the next three decades, mitigating impacts of climate change, and making agricultural production resilient. More productivity is expected from agricultural lands, but intensification of production could further impact the integrity of our finite surface water and groundwater resources. Integrating perennial bioenergy crops in agricultural lands could provide biomass for biofuel and potential improvements on the sustainability of commodity crop production. This article provides an overview of ways in which research has shown that perennial bioenergy grasses and short rotation woody crops can be incorporated into agricultural production systems with reduced indirect land use change, while increasing water quality benefits. Current challenges and opportunities as well as future directions are also highlighted.

Cacho, J. F.↗
DOE OSTI2013

Advancing sustainable bioenergy: Evolving stakeholder interests and the relevance of research

The sustainability of future bioenergy production rests on more than continual improvements in its environmental, economic, and social impacts. The emergence of new biomass feedstocks, an expanding array of conversion pathways, and expected increases in overall bioenergy production are connecting diverse technical, social, and policy communities. These stakeholder groups have different and potentially conflicting values and cultures, and therefore different goals and decision making processes. Our aim is to discuss the implications of this diversity for bioenergy researchers. The paper begins with a discussion of bioenergy stakeholder groups and their varied interests, and illustrates how this diversity complicates efforts to define and promote sustainable bioenergy production. We then discuss what this diversity means for research practice. Researchers, we note, should be aware of stakeholder values, information needs, and the factors affecting stakeholder decision making if the knowledge they generate is to reach its widest potential use. We point out how stakeholder participation in research can increase the relevance of its products, and argue that stakeholder values should inform research questions and the choice of analytical assumptions. Finally, we make the case that additional natural science and technical research alone will not advance sustainable bioenergy production, and that important research gaps relate to understanding stakeholder decision making and the need, from a broader social science perspective, to develop processes to identify and accommodate different value systems. While sustainability requires more than improved scientific and technical understanding, the need to understand stakeholder values and manage diversity presents important research opportunities.

Johnson, Timothy L↗
DOE OSTI2015

Bioenergy and biodiversity: Key lessons from the Pan American region

Understanding how large-scale bioenergy production can affect biodiversity and ecosystems is important if society is to meet current and future sustainable development goals. A variety of bioenergy production systems have been established within different contexts throughout the Pan American region, with wide-ranging results in terms of documented and projected effects on biodiversity and ecosystems. The Pan American region is home to the majority of commercial bioenergy production and therefore the region offers a broad set of experiences and insights on both conflicts and opportunities for biodiversity and bioenergy. This paper synthesizes lessons learned focusing on experiences in Canada, the United States, and Brazil, regarding the conflicts that can arise between bioenergy production and ecological conservation, and benefits that can be derived when bioenergy policies promote planning and more sustainable land management systems. Lastly, we propose a research agenda to address priority information gaps that are relevant to biodiversity concerns and related policy challenges in the Pan American region.

09 BIOMASS FUELS↗