This data product is an assembly of best available and citable information from around the globe on current biomass uses, and potential for additional sustainable biomass supplies. This dataset was compiled through an inventory and review of current sources of data and biomass resource assessments, including recent (since 2018) national, regional, and global assessments. An initial list of assessments identified (report version 1) have been assembled based on outreach and literature review.
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This dataset provides additional variables for modelers and other interested stakeholders for yield assumptions for modeled energy crops on agricultural land in the CONUS, as modeled by the POLYSYS model.
The yield unit was changed from lb/ac to dt/ac post-processing.
V0.1 changes include: tillage for subclass like 'energy crop' is now '[null]' and for subclass = 'Intermediate oilseeds' 'till' is now 'CT' (Conventional Tillage), format now uses pipe (|) delimiter.
Data from emerging resources, CO2 from chapter 7.3 in the 2023 Billion-Ton Report. Please access the data through the BT23 Data Portal or directly at https://bioenergykdf.ornl.gov/bt23-co2-high-purity-download and https://bioenergykdf.ornl.gov/bt23-co2-total-supply-download
Data from Emerging Resources: Macroalgae. Please access the data through the BT23 Data Portal or directly at https://bioenergykdf.ornl.gov/bt23-macro-algae-download
Please cite as:
A. Coleman. 2024, Data from Emerging Resources: Macroalgae of Chapter 7.2 in the 2023 Billion-Ton Report. Version 0.0.1, Bioenergy Knowledge Discovery Framework (KDF) Data Center, https://doi.org/10.23720/BT2023/2282995
This dataset includes waster resources prepared for BT23 Chapter 3. Please access the data through the BT23 Data Portal or directly at https://bioenergykdf.ornl.gov/bt23-wastes-download
Please cite as:
Milbrandt, A., and A. Badgett. 2024, Data from Biomass from waste streams, of Chapter 3 in the 2023 Billion-Ton Report. Version 0.0.1, Bioenergy Knowledge Discovery Framework (bioenergyKDF)Data Center, https://doi.org/10.23720/BT2023/2282886
This dataset includes POLYSYS model output prepared for BT23 Chapter 5. Please access the data through the BT23 Data Portal or directly at https://bioenergykdf.ornl.gov/bt23-agricultural-download
This dataset includes ForSEAM and BioSUM model output prepared for BT23 Chapter 4, as well as USDA-FS Forest Inventory Analysis datasets used to calculate waste biomass from the forested land base. Please access the data through the BT23 Data Portal or directly at https://bioenergykdf.ornl.gov/bt23-forestry-download
A-customized-dataset-for-national-timberland-resources-modeled-with-ForSEAM
This dataset includes longitudinal measurements of water quality in four streams and rivers across the United States that were collected using the AquaBOT, an unmanned surface vehicle equipped with water quality sensors developed as part of a BETO-funded project ('Spatially resolved measurements of water quality indicators within a bioenergy landscape'). Measured water quality indicators include: nitrate concentration, temperature, specific conductivity, dissolved oxygen, turbidity, chlorophyll, and pH.
Short Rotation Woody Crop Production Scenarios Simulated for Idaho National Laboratory-ORNL Collaborations, June 2021.
Simulations under this dataset were targeted to a specific fuelshed in Iowa.
Integrated land management (ILM) applications were targeted under this research, although the results of these simulations are at the county level; downscaling post-processing will be applied.
Contact information about the submitter of this metadata record:
Author list: Maggie Davis, Matt Langholtz, Laurence Eaton, Chad Hellwinkel
Who should be contacted with questions relating to the data? (Principal investigator or primary developer of data product): Maggie Davis, davismr@ornl.gov
The goal of this repository is to promote transparency and ease-of-access to the U.S. Department of Energy Bioenergy Technologies Office (BETO) supported public studies involving techno-economic analysis (TEA). As such, this database summarizes the economic and technical parameters associated with the modeled biorefinery processes for the production of biofuels and bioproducts, as presented in a range of published reports and papers.
on environment friendly and socio-economically sustainable renewable energy sources. However, commercial production of bioenergy is constrained by biomass supply uncertainty and associated costs. This study presents an integrated approach to determining the optimal biofuel supply chain considering biomass yield uncertainty. A two-stage stochastic mixed integer linear programming is utilized to minimize the expected system cost while incorporating yield uncertainty in the strategic level decisions related to biomass production and biorefinery investment.
Perennial grasses are touted as sustainable feedstocks for energy production. Such benefits, however, may be offset if excessive nitrogen (N) fertilization leads to economic and environmental issues. Furthermore, as yields respond to changes in climate, nutrient requirements will change, and thus guidance on minimal N inputs is necessary to ensure sustainable bioenergy production.
Sustainable production of algae will depend on understanding trade-offs at the energy-water nexus. Algal biofuels promise to improve the environmental sustainability profile of renewable energy along most dimensions. In this assessment of potential US freshwater production, we assumed sustainable production along the carbon dimension by simulating placement of open ponds away from high-carbon-stock lands (forest, grassland, and wetland) and near sources of waste CO 2 .
Practicing agriculture decreases downstream water quality when compared to non-agricultural lands. Agricultural watersheds that also grow perennial biofuel feedstocks can be designed to improve water quality compared to agricultural watersheds without perennials. The question then becomes which conservation practices should be employed and where in the landscape should they be situated to achieve water quality objectives when growing biofuel feedstocks.