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 supporting information (SI) prepared for the manuscript "Winter rye biomass can be an abundant and affordable US energy resource." It summarizes research developed through collaboration between USDA and Penn State winter rye subject matter experts and economists from ORNL's Bioresource Science and Engineering Group.

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 (Feyereisen et al. 2013). We used county-level regression model yields for the scenarios where cereal rye is planted 2 days after the prior corn grain or soybean harvest, and the subsequent corn or soybean crop is planted 7 days after the rye harvest on land in continuous corn and corn/soy rotation. These county-scale winter rye yields were inputs (SI.1) for the POLYSYS economic model (Ugarte and Ray 2000) used to estimate future agricultural biomass supplies for the DOE 2023 Billion-Ton Report (DOE 2024). Regional agronomic budget inputs (e.g., fertilizer and seeding rates, labor and machinery costs) were developed based on Malone et al. (2023) and the assumption that rye would be harvested and hauled wet in a wagon to an on-farm pit or silage bunker rather than being baled (SI.2).

Modeled fertilizer applications were 45 kg/ha of N, 15 kg/ha of P, and 56 kg/ha of K (41 lbs/acre of N, 13 lbs of P and 50 lbs/ac of K). The N fertilizer application rate was based on results from several studies across 6 states in the midwestern and southeastern US where responses to N fertilization rates from 0 to 120 kg/ha were mixed (Malone et al. 2022; Malone et al. 2023, Crespo et al. 2025; Balkcom et al. 2018). In a 13-year randomized plot trial, Crespo et al. (2024) observed that winter rye shoot biomass responded to both warmth (growing degree days) and precipitation. In a two-year trial with adequate rainfall both years, Crespo et al. (2025) observed that rye responded more to warmer spring temperatures than to N fertilizers. In a cool spring with yields < 3 Mg/ha supplemental N fertilization did not improve yields compared with natural N mineralization from soil organic matter (0 fertilizer N), but in a warmer spring when there were sufficient growing degree days, supplemental N fertilizer at 30 and 60 kg N/ha resulted in higher yields. While we used the midpoint of 30 and 60 kg/ha (45 kg N/ha) for this study’s national projections, location-specific fertilizer recommendations should be based on local climate and soil conditions.

Western US counties where evaporation exceeds precipitation were excluded from consideration since our budgets do not account for irrigation; unirrigated rye in these areas would consume soil water needed for corn and soybeans. In the eastern US with ample spring soil water, we assumed rainfed winter rye even if the summer crop is irrigated; so winter rye was allowed in these counties if profitable given county yields and costs.

We started POLYSYS with the 2023 USDA agricultural baseline and ran the model out to 2041 with annual timesteps and price intervals to simulate a mature market demand for biomass. Winter rye production was limited to locations where the net returns of corn/rye/soy rotations were greater than the net returns from corn/soy rotations. County-level biomass estimates (SI.3) and production areas (SI.4) are summarized here for three biomass farmgate rice offerings in dollars per dry US short ton: $30/dt, $70/dt, and $150/dt. At a price offering of $150/dt ($165/Mg), we found a potential winter rye biomass supply of 214 M dry short tons (194 million Mg) produced across 80.7 million acres (32.7 million ha).

We modeled winter rye production relative to a “pessimistic case” of 10% lower rye yields and 10% higher production costs relative to an “optimistic case” of 10% rye yield improvements and 10% lower production costs (SI.5). With improvements in crop yield and harvesting efficiency, winter rye biomass production could increase to 230 million Mg yr-1. We then compared the economic returns and acreages of winter rye to other bioenergy crops and residues recently modeled for DOE's national biomass resource assessment. We found that winter rye is competitive with other cellulosic feedstocks across a range of prices and can produce more biomass at a lower cost than perennial grasses (switchgrass and miscanthus), crop residues (corn stover and wheat straw), and woody biomass (poplar and willow) (SI.5).

Because this crop is grown on land that would otherwise be fallow, we found that high price offerings and large volumes of winter rye would have little or no impact on national 20-year average equilibrium food crop prices (SI.6). Winter rye is easier to establish and remove than perennial crops like miscanthus or willow, meaning that it has lower risk and is more likely to expand across acres than other dedicated energy crops (SI.7).

We calculated energy and fertilizer yields from the potential 194 million Mg annual biomass supply at a price offering of $165/Mg by assuming the rye was anaerobically digested to produce renewable natural gas (RNG). We used previously published biogas production rates (Herbstritt et al. 2022) and calculated net energy based on both agronomic and digester operations as well as an average round trip transportation distance of 129 km to a centralized digester (SI.2). For this biomass production quantity, annual bioenergy yields would be 1.59 EJ per year (SI.8). 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 (SI.8).

The 8 referenced file attachments of supporting information (SI) are provided below the Citations. 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.

Citations:
Balkcom, K.S., Duzy, L.M., Arriaga, F.J., Delaney, D.P. and Watts, D.B. (2018), Fertilizer Management for a Rye Cover Crop to Enhance Biomass Production. Agronomy Journal, 110: 1233-1242. https://doi.org/10.2134/agronj2017.08.0505.
Crespo, C., Malone, R. W., Radke, A., Kovar, J. L., Emmett, B. D., Feyereisen, G. W., Thorp, K. R., Richard, T., & O'Brien, P. L. (2025). Rye performance in central Iowa under different seeding and nitrogen fertilizer rates. Agronomy Journal, 117, e70112. https://doi.org/10.1002/agj2.70112.
Crespo, C., O’Brien, P. L., Ruis, S.J., Kovar, J.L., Kaspar, T.C. (2024). Thermal time and precipitation dictate cereal rye shoot biomass production, Field Crops Research 315, https://doi.org/10.1016/j.fcr.2024.109473.
Feyereisen, G. W., G.T.T. Camargo, R.E. Baxter, J.M. Baker, and T.L. Richard (2013). Cellulosic biofuel potential of a winter rye double crop across the US corn-soybean belt. Agronomy Journal 105(3):631-642.
Herbstritt S., T. L. Richard, S. H. Lence, H. Wu, P. L. O’Brien, B. D. Emmett, T. C. Kaspar, D. L. Karlen, K. Kohler, and R. W. Malone (2022). Rye as an energy cover crop: management, forage quality, and revenue opportunities for feed and bioenergy. Agriculture 12:1691.
Malone, R.W., O’Brien, P.L., Herbstritt, S., Emmett, B.D., Karlen, D.L., Kaspar, T.C., Kohler, K., Radke, A., Lence, S.H., Wu, H., and Richard, T.L. (2022). Rye soybean double-crop: planting method and N fertilization effects in the North Central US. Renewable Agriculture and Food Systems 1–12. https://doi.org/10.1017/S1742170522000096
Malone R.W., A. Radke, S. Herbstritt, H. Wu, Z. Qi, B. D. Emmett, M. J. Helmers, L. A. Schulte, G. W. Feyereisen, P. L. O’Brien, J. L. Kovar, N. Rogovska, E. J. Kladivko, K. R. Thorp, T. C. Kaspar, D. B. Jaynes, D. L. Karlen, and T. L. Richard (2023). Harvested winter rye energy cover crop: Multiple benefits for North Central US. Environmental Research Letters 18:(7), 074009.
Ugarte D.G. and D. E. Ray (2000). Biomass and bioenergy applications of the POLYSYS modeling framework. Biomass and Bioenergy 18(4), 291-308.
US Department of Agriculture (USDA). Agricultural Projections to 2034. Office of the Chief Economist, World Agricultural Outlook Board, US Department of Agriculture. Prepared by the Interagency Agricultural Projections Committee. Long-Term Projections Report OCE-2025-1, 114 pp. (2025).
US Department of Energy (DOE). 2023 Billion‐Ton Report: An Assessment of US Renewable Carbon Resources. M. H. Langholtz (Lead). Oak Ridge, TN: Oak Ridge National Laboratory. ORNL/SPR-2024/3103 (2024). https://www.energy.gov/eere/bioenergy/2023-billion-ton-report-assessmen…
US Department of Agriculture (USDA). Agricultural Projections to 2034. Office of the Chief Economist, World Agricultural Outlook Board, US Department of Agriculture. Prepared by the Interagency Agricultural Projections Committee. Long-Term Projections Report OCE-2025-1, 114 pp. (2025).

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.