Supporting Data

The residue retention requirement represents the minimum quantity of crop residue (dry tons per acre per year) that must remain on the field to satisfy soil sustainability constraints, including maintenance of soil organic carbon and limits on wind and water erosion. See Metadata description for residue retention coefficients.pdf for more detailed information.

The dataset is comprised of "MuthFiles_Version2025POLYSYS_ChadHellwin.zip" corresponding to the version used in the POLYSYS model for the Billion-Ton Report; Residue removal coefficients to KDF.7z which will open an Excel file (extension .xlsx) by the same name when unzipped; MuthMapping_MDavis-Oct30-2025.7z which when unzipped using 7zip or similar service will deliver several individual maps of the datasets and a Jupyter Notebook (.ipynb extension) to visualize the data and produce the maps delivered in this zipped file.

Note that residue retention values were derived from process-based modeling (EPIC and RUSLE) as reported in Muth et al.(2012). These values are not percentages or fractions. A value of 10 tons/acre/year should be interpreted as: Residue removal is effectively constrained (no removal feasible) under modeled conditions. Values vary by: Crop type, County, Tillage system, Yield scenario, and Year.

For additional information, please see BT16 resources as well as:
Muth, D. J., et al. (2012). Sustainable agricultural residue removal for bioenergy: A spatially comprehensive US national analysis. Applied Energy. http://dx.doi.org/10.1016/j.apenergy.2012.07.028

This page provides datasets and calculations prepared for the manuscript "Winter rye biomass can be an abundant and affordable US energy resource" through collaboration between ORNL, USDA, and Penn State researchers. Winter rye (Secale cereale L.) was modeled as a harvested crop grown during the fallow period in continuous corn fields or in corn and soybean rotations. We obtained 14-year average winter rye yield simulations from the RyeGro soil-plant-atmosphere model previously developed for 30 US locations and six planting and harvesting date scenarios and used these as inputs to the POLYSYS economic model. Regional agronomic budget inputs assumed (1) fertilizer applications of 41 lbs/acre of N, 13 lbs of P and 50 lbs/ac of K, and (2) that rye would be harvested and hauled wet in a wagon to an on-farm pit or silage bunker rather than being baled. County-scale production estimates from the POLYSYS model at three different price offerings ($30/dt, $70/dt, and $150/dt), and calculations of net energy from 214 M dry short tons (194 million Mg) produced across 80.7 million acres (32.7 million ha) are all provided here as Excel spreadsheet attachments. We calculated that for this biomass production quantity, annual bioenergy yields would be 1.59 EJ per year. If all of this winter rye were converted to natural gas through anaerobic digestion, we estimate that there would be enough nitrogen in the digestate to recover 1.3 million Mg of N fertilizer. These calculations are detailed in the attached Excel spreadsheet named "Net_Energy_and_Fertilizer_Calculations" found at the bottom of this page.

Additional POLYSYS outputs for the Winter Rye scenarios exceed the 8 MB file size limit for this site but are available upon request. Please contact biokdfadmin@ornl.gov for access.

The Ag Budget Operations Table presents a detailed compilation of operations along with their corresponding parameters and material inputs for both conventional and energy crops used in the Billion Ton 2023 study. This dataset encompasses a range of activities, including land preparation, planting, fertilization, pest management, land maintenance, and harvesting.
Key fields within the dataset include equipment data, fertilizer and chemical application details, and seed information. Additionally, the dataset contains cost metrics such as purchase costs and labor costs, enabling users to effectively analyze the financial aspects of crop production.
To enhance understanding of the data, a supplementary spreadsheet is provided, containing field definitions that clarify the terminology and metrics used throughout the dataset.

The Ag Budget Operations Table presents a detailed compilation of operations along with their corresponding parameters and material inputs for both conventional and energy crops used in the Billion Ton 2023 study. This dataset encompasses a range of activities, including land preparation, planting, fertilization, pest management, land maintenance, and harvesting.
Key fields within the dataset include equipment data, fertilizer and chemical application details, and seed information. Additionally, the dataset contains cost metrics such as purchase costs and labor costs, enabling users to effectively analyze the financial aspects of crop production.
To enhance understanding of the data, a supplementary spreadsheet is provided, containing field definitions that clarify the terminology and metrics used throughout the dataset.

Yield (i.e., tons of biomass per acre per year) is a key driver of production potential for many biomass resources. For agricultural resources, crop- and county-specific yields are an input to the economic modeling used to assess biomass production capacity in the BT23. Yields for agricultural biomass resources were derived from field trials from the Sun Grant Initiative Regional Feedstock Partnership, which served the basis for calibration of county yields (see 2016 Billion-Ton Report section 4.2.4)
For the 2016 and 2023 Billion-Ton reports, a workflow was established to provide a series of yields including biophysical, harvestable potential, future year- and scenario-specific potential, stand-age specific potential, and final solution yields. These datasets are comprised of several yield types including 1) PRISM Yield, 2) Base Harvestable Mean Annual Increment, 3) Mature Harvestable Yield (or MAI) by scenario, 4) Harvestable Yield for the Complete Crop Rotation by Scenario, and 5) Solution Yield by Scenario. Each yield type is defined below in the metadata.

This write up summarizes the potential for biobased adhesives to be sourced from various material, specifically focusing on the following relevant factors:
1. Current biomass availability,
2. Market costs
3. Locations of industry/supply
4. Projections on how these materials will increase in availability according to their expected increased uses.

This project contributes to understanding and enhancing socioeconomic and environmental benefits of biofuels through modeling the effect of prices and policy incentives on fuel markets for “hard-to-decarbonize” transportation sectors. The main analytical tool used in this project is the BioTrans model, originally developed to assess and quantify the economic and energy security benefits of biofuels for light-duty vehicles and bioproducts. This project restructured and updated the BioTrans model to assess biofuels for the hard-to-decarbonize transportation sectors such as the aviation and shipping.

The BioTrans model is a market equilibrium model assessing the biofuel supply chain for a 30-year horizon with annual periods. It is a national (United States) model and has states as its spatial units. The model maximizes social surplus, which implies minimizing the costs, while meeting transportation fuel demands. While it takes transportation fuel markets into account endogenously, land allocation decisions and non-biofuel uses of biomass are considered exogenously. The model considers potential synergies or competition for the use of biomass among the different transportation segments as well as the competition between new biofuels and incumbent petroleum-based fuels.

The diagram in Figure 1 summarizes the main components included in BioTrans as of September 2025.

Figure 1. Main components included in BioTrans

The biomass feedstocks and petroleum products in blue rectangles are those for which the model includes supply curves, and the transportation segments in red boxes are those for which the model includes demand curves. The intermediate activities reflect the steps required to convert biomass into biofuel, and the intermediate products are biofuels required for blending and retail. Each commodity must satisfy a material balance equation so that its sources and sinks match with each other. 

The ability to explore the interaction of federal and state-level biofuel policies and their impact on the volume and mix of biofuels produced in the United States is one of the key attributes of the model. Figure 2 shows the list of federal and state-level biofuel-related policies and incentives contained in the BioTrans model as of September 2025.

Figure 2. Federal and state-level biofuel-related policies and incentives

The code for the BioTrans model is available at https://code.ornl.gov/bioenergy/biotrans_model

This International Feedstocks data portal supports the Global Biomass Resource Assessment, a multi-country government-led initiative dedicated to advancing the global transition to a bioeconomy. This product shares data assembled from citable sources around the globe, as reported for current biomass production as well as potential additional future production in some cases. Data were compiled into consistent classes based on the most recent reports received (ranging from 2018 to 2024).

The results from this new global sustainable supply assessment will allow scientists, policymakers, and industry leaders to explore potential sources of biomass as a foundation for a global bioeconomy, supporting fuels, chemicals, materials and other products. The assessment was conducted by researchers at the U.S. Department of Energy(DOE) Oak Ridge National Laboratory (ORNL), with funding provided by the U.S. Department of State, and managed through DOE’s Bioenergy Technologies Office (BETO), on behalf of the CEM Biofuture Initiative and Mission Innovation. This data includes biomass resources available in many developing economies which often do not have fully advanced biomass industries. The assessment also aims to address the need for internationally accepted benchmarks quantifying sustainable biomass feedstock supplies that can be available to support a growing bioeconomy.

Download the Mapping and Synthesis of International Biomass Supply Assessments (pdf, January 2025) document for more information.

The link below provides access to the data which can be filtered by country of interest and resource, as well as timeframe for the available biomass. The data are being shared based on the information received to date (references to sources are noted for each reported nation). We aim to improve and update this preliminary version of the data set in the future, based on user feedback. Please send suggestions for improvement and references to additional sources of data, or corrections to the reported data. Data comments can be sent to biomass.updates@ornl.gov

International Feedstocks Data View

This data can be filtered by country and downloaded for further analysis. For example, the country of Uruguay is summarized below for available resources by year of production.

This dataset contains data on forest production. The forestry products in this dataset includes hardwood, softwood, and mixed, and the dataset was obtained from the database of the 2023 Billion-Ton Report (Davis et al., 2024). The intended use is for the Feedstock Production Emissions to Air Model (FPEAM).

If you would also like access to this dataset, please use the "contact" button for a request to our research staff.

This dataset contains data on agricultural crop production. The agricultural crop in this dataset includes barley, corn, cotton, grain sorghum, hay, oats, rice, soybeans, and wheat, and the dataset was obtained from the database of the 2023 Billion-Ton Report (Davis et al., 2024) for the Feedstock Production Emissions to Air Model (FPEAM).

For access to this dataset, please use the contact form and indicate the dataset by name.