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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.

Organization:
DOE
Author(s):
Matthew H Langholtz

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

Organization:
DOE
Author(s):
Anelia Milbrandt , Alex Badgett

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

Organization:
DOE
Author(s):
Maggie Davis , Lixia Lambert , Ryan Jacobson , Consuelo Brandeis , Jeremy Fried , Burton English

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.

Organization:
DOE
Author(s):
Natalie A. Griffiths, Peter S. Levi, Jeffery S. Riggs, Christopher R. DeRolph, Allison M. Fortner, Jason K. Richards

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.

Organization:
DOE
Author(s):
Maggie R. Davis
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

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

Organization:
DOE
Author(s):
Maggie Davis , Matt Langholtz , Laurence Eaton , Chad Hellwinkel
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

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.

Organization:
DOE
Author(s):
Christopher Kinchin
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

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.

Author(s):
Sharma, B. P. , T. E. Yu , B. C. English , C. Boyer , J. A. Larson

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.

Organization:
DOE
Author(s):
Huaihai Chen , Zhongmin Dai , Henriette I. Jager , Stan D. Wullschleger , Jianming Xu , Christopher W. Schadt
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

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 .

Organization:
DOE
Author(s):
Henriette I. Jager , Rebecca A. Efroymson , Latha M. Baskaran
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

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.

Organization:
DOE
Author(s):
Jasmine A.F. Kreig , Herbert Ssegane , Indrajeet Chaubey , Maria C. Negri , Henriette I. Jager
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

New domestic, renewable energy resources must be considered to increase energy security in the U.S. Ethanol production through second-generation (cellulosic) feedstocks will help the U.S. meet the legislative Renewable Fuel Standard, which mandates 36 billion gallons of renewable fuels by 2022. However, conversion of cropland to meet the cellulosic feedstock production goals may have unforeseen environmental consequences.

Author(s):
David E. Gorelick , Latha M. Baskaran , Henriëtte I. Jager