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.
material_class: This indicates the label to denote land source or analysis source corresponding to the forest land chapter of the 2023 Billion-Ton Report.
subclass: This indicates the class of biomass.
resource_name: This indicates the type of resource.
diacls: This indicates the class of tree diameter. Class 1 has a diameter at breast height (DBH) that is greater than 11-inch, Class 2 has a DBH that is between 5- and 11-inch, and Class 3 has a DBH that is less than 5-inch.
owner: This indicates the owner such as public, private, and null or unknown.
fips: This is a geographically defined variable corresponding to counties provided as a 5-digit code.
county: This indicates the name of the county.
state: This indicates the name of the state.
County square Miles: This indicates the total area of the county in square miles including water.
scenario_name: This indicates the name of the scenario defined in the 2023 Billion-Ton Report. “mm” indicates mature market scenario, and it also contains “low”, “high”, and “emerging” scenarios.
scenario_price_offered: This indicates a price offered for a ton of biomass.
production: This indicates the total production of the forestry biomass in dry ton.
production_unit: This indicates the unit of production.
production_energy_content: This indicates the total energy contents in BTU which is production tons multiplied by BTU/ton.
energy_content_unit: This indicates the unit of energy content.
production_density_dtpersqmi: This indicates a production divided by the total area of the county.
harvest_costs: This indicates the cost of harvesting.
harvest_area: This indicates the total harvested area in acres.
harv_area_unit: This indicates the unit of harvested area.
lipid_based: This indicates either the biomass is based on lipid or not.
ash_percentage: This indicates the content of ash in percentage.
This dataset contains harvesting, chipping, and production cost data for forestland production by region and forest harvest system. The dataset supports Biomass from the forested land base analysis in the BT23 (Davis et al., 2024) and subsequent modeling using the Forest Sustainable and Economic Analysis Model (ForSEAM). The cost data was updated by Burton English and is in 2014 dollars and 2021 dollars. Data sources can be found in the accompanying PDF, ‘2021 Biomass Production Costs for the 2024 Billion Ton Analysis’, and the details can be found in the accompanying Microsoft Word file.
Cost_by_FHS_and_Region.csv is a comma-separated file that holds the following variables: Forest_Harvest_Systems: This is for different forest silvicultural and harvest methods.
Region: This is for different production cost zones of the CONUS as defined by ForSEAM.
Slope_over_40%: This is a binary variable to indicate if the slope exceeds 40%.
CutToLength: This is a binary variable to indicate if the cut-to-length method is used.
Cut: This indicates the forest management practice of either thinning or clearcutting.
Type: This indicates the type of forest.
Harverst_Production_Costs_2021$_per_bdt: The harvest costs of production per bone dry ton (bdt) in 2021 dollars.
Chipping_Costs_2021$_per_bdt: The costs of production to chip the biomass per bone dry ton (bdt) in 2021 dollars.
Total_Costs_2021$_per_bdt: The costs of production to harvest and chip the biomass per bone dry ton (bdt) in 2021 dollars.
Harverst_Production_Costs_2014$_per_bdt: The harvest costs of production per bone dry ton (bdt) in 2014 dollars.
Chipping_Costs_2014$_per_bdt: The costs of production to chip the biomass per bone dry ton (bdt) in 2014 dollars.
Total_Costs_2014$_per_bdt: The costs of production to harvest and chip the biomass per bone dry ton (bdt) in 2014 dollars.
Total_Forest_Production_Costs_2021$_per_bdt: The total production costs of forestland biomass per bone dry ton (bdt) in 2021 dollars.
Timber_Costs_2014$_per_dry_ton: The costs for timber per dry ton biomass in 2014 dollars.
Chipper_Costs_2014$_per_dry_ton: The costs for chipper per dry ton biomass in 2014 dollars.
Total_Costs_2014$_per_dry_ton: The costs for timber and chipper per dry ton biomass in 2014 dollars.
Cost_by_Region.csv is a comma-separated file that holds the following variables:
Region: This is for different production cost zones of the CONUS as defined by ForSEAM.
Slope_over_40%: This is a binary variable to indicate if the slope exceeds 40%.
CutToLength: This is a binary variable to indicate if the cut-to-length method is used.
Type: This indicates the type of forest.
Cut: This indicates the forest management practice of either thinning or clearcutting.
Forest_Production_Costs_2021$_per_bdt: The total production costs of forestland biomass per bone dry ton (bdt) in 2021 dollars.
Timber_Costs_2014$_per_dry_ton: The costs for timber per dry ton biomass in 2014 dollars.
Chipper_Costs_2014$_per_dry_ton: The costs for chipper per dry ton biomass in 2014 dollars.
Total_Costs_2014$_per_dry_ton: The costs for timber and chipper per dry ton biomass in 2014 dollars.
Cost_by_FHS.csv is a comma-separated file that holds the following variables:
Forest_Harvest_Systems: This is for different forest silvicultural and harvest methods.
Cut: This indicates the forest management practice of either thinning or clearcutting.
Harverst_Production_Costs_2021$_per_bdt: The harvest costs of production per bone dry ton (bdt) in 2021 dollars.
Chipping_Costs_2021$_per_bdt: The costs of production to chip the biomass per bone dry ton (bdt) in 2021 dollars.
Total_Costs_2021$_per_bdt: The costs of production to harvest and chip the biomass per bone dry ton (bdt) in 2021 dollars.
Harverst_Production_Costs_2014$_per_bdt: The harvest costs of production per bone dry ton (bdt) in 2014 dollars.
Chipping_Costs_2014$_per_bdt: The costs of production to chip the biomass per bone dry ton (bdt) in 2014 dollars.
Total_Costs_2014$_per_bdt: The costs of production to harvest and chip the biomass per bone dry ton (bdt) in 2014 dollars.
What’s in the 2023 Billion-Ton Report?Oak Ridge National Laboratory’s Matthew Langholtz provides a short background summary for each of the resource classes and market scenarios explored in the 2023 Billion-Ton Report.
BioenergyKDF: How to access the dataOak Ridge National Laboratory’s Maggie Davis shares how to access the resources from the 2023 Billion-Ton Report using the Bioenergy KDF data portal.
2023 Billion-Ton Report: MacroalgaeAnne Otwell, a contractor in the Department of Energy's Bioenergy Technologies Office, highlights the findings about macroalgae from the 2023 Billion-Ton Report.
The U.S. Department of Energy Bioenergy Technology Office's (BETO's) 2023 Billion-Ton Report (BT23) is an assessment of renewable carbon resources potentially available in the United States. BT23 explores these resources in terms of quantity, price, geographical density and distribution, and market maturity. Resource quantities in this report are limited by specified economic and environmental sustainability constraints. Good practices are needed to ensure biomass production has positive environmental outcomes.
BT23 supports BETO's mission, particularly the 2023 Multi-Year Program Plan. To access 2023 Billion-Ton Report PDFs, appendices, and high-level messages, navigate to the 2023 Billion-Ton Report landing page at https://energy.gov/eere/bioenergy/2023-billion-ton-report-assessment-us… on the U.S. Department of Energy Bioenergy Technologies Office website.
Please cite the 2023 Billion-Ton Report as: U.S. Department of Energy. 2024. 2023 Billion‐Ton Report: An Assessment of U.S. Renewable Carbon Resources. M. H. Langholtz (Lead). Oak Ridge, TN: Oak Ridge National Laboratory. ORNL/SPR-2024/3103. doi: 10.23720/BT2023/2316165.
a. Cotton gin trash and rice hulls, totaling 2.1 and 1.3 million tons per year in all scenarios, were omitted in error from the BT23 figures and initial data release. Data for these resources were added to the BT23 Agricultural Download on April 23rd, 2024. Methods are described in BT23 Appendix C, pages 6-7.
b. Orchard prunings, totaling 6 million tons per year in all scenarios, were classified as agricultural processing waste in the report, but are now classified as agricultural residues in the data. The combined changes from cotton gin trash, rice hulls, and orchard prunings cause agricultural residues to increase by 6 million tons per year and agricultural processing wastes to decrease by 2.5 million tons per year, as compared to values provided in Summary Table ES-1. This is less than a 1% change in the national results in all scenarios.
Constraints
Biomass resources in the 2023 Billion-Ton Report are presented as production capacity under specified environmental constraints, prices, and market scenarios. Modeling varies by resource class. For example:
Agricultural residue production capacity is limited to about 1/3 of national total by retention constraints for soil conservation.
Timberland resources are constrained such that total harvests are less than net growth, and sensitive areas are excluded.
Energy crop production capacity is modeled as producer response to biomass markets in addition to projected demands for food, feed, fiber, and export. More detail is provided this summary document and in the report.
Errata
Data for rice hulls and cotton gin trash are missing in the report, but have been added in the data portal (see data update information in “Featured Data Updates”)
In Table 1.5 on page 15, the phrase “except where cable systems are in use (Northwest United States)” is an error. Cable harvesting systems were modeled for conventional timber products, but biomass from logging residues from cable harvesting systems were not included in the analysis. This assumption to exclude logging residues from cable harvesting systems can be questioned, because cable harvesting systems produce piles of logging residues at collection.
In Figure ES-1 on page xix, labeling of microalgae and macroalgae in the top right of the figure are switched. The correct labeling should follow the symbology provided in the lower right of the figure, i.e. 169 million tons per year of microalgae at a weighted average price of $650 per ton, and 79 million tons per year of macroalgae at $500 per ton.
In Figure ES-6 on page xxviii, under “Remaining timberland (unharvested)”, the "/year" was included in error. This is because remaining timberland is a stock, not an annual rate of production. However, the “/year” is correct for the “Harvest for conventional forest products” and “Reference scenario (small-diameter trees)” categories in the same figure.
In Figure 5.11 on page 116, the primary and secondary y-axis scales are misaligned. The axes values should align with the horizontal lines.
In the text box on page 23, “During CO2 fermentation some of this recycled CO2 can be harnessed…” should instead say “During fermentation some of this recycled CO2 can be harnessed…”
The following errors in v0.1 of waste data were corrected in v1.0:
The wet waste and solid waste price data released were erroneously inflated 14%, and has been reduced to 0 to report as 2022$. The wastes summary in Table 3.1 remains unchanged as $2022.
A moisture content of 6% was assumed for waste paper, which was corrected to 5.5%, causing an increase of 447,000 dry tons of waste paper (i.e, 0.5% of waste paper).
Langholtz, Matthew H., Davis, Maggie, Hellwinckel, Chad, De La Torre Ugarte, Daniel, Efroymson, Rebecca, Jacobson, Ryan, Milbrandt, Anelia, Coleman, Andre, Davis, Ryan, Kline, Keith L., Badgett, Alex, Curran, Scott, Schmidt, Erik, Theiss, Timothy, Fried, Jeremy, English, Burton, Lambert, Lixia, Cook, Hope, Field, John, Abt, Robert, Parish, Esther, Rossi, David, Abt, Karen, Brandt, Craig, Saltiel, Troy, Davis, Kristen, Otwell, Anne, Clark, Robin, Miller, Lee, Brandeis, Consuelo, Oyedeji, Oluwafemi, Klein, Bruno, Wiatrowski, Matthew R., Hawkins, Troy, Ou, Longwen, Singh, Udayan, Zhang, Jingyi, Gao, Song, Snowden-Swan, Lesley, Valdez, Peter, Xu, Yiling, Zhu, Yunhua, De angelo, Julianne, Nepal, Prakash, Prestemon, Jeffery, Champion, Kathleen, Saenz, Benjamin, Harrison, Eliza, O dea, Claire, Cooney, Gregory, Hoffmann, Jeffrey, Shell, Michael, and Walker, Lee. 2023 Billion-Ton Report: An Assessment of U.S. Renewable Carbon Resources. United States: N. p., 2024. Web. doi:10.2172/2441098.
[Equivalent to: U.S. Department of Energy. 2024. 2023 Billion‐Ton Report: An Assessment of U.S. Renewable Carbon Resources. M. H. Langholtz (Lead). Oak Ridge, TN: Oak Ridge National Laboratory. ORNL/SPR-2024/3103. doi: 10.23720/BT2023/2316165.]
Matthew H Langholtz , Maggie Davis , Chad Hellwinckel , Daniel DeLaTorre Ugarte , Rebecca Efroymson , Ryan Jacobson , Anelia Milbrandt , Andre Coleman , Ryan Davis , Keith L. Kline , et al.