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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

NREL's energy-water modeling and analysis activities analyze the interactions and dependencies of water with the dynamics of the power sector and the transportation sector. A variety of models and tools are utilized to consider water as a critical resource for power sector development and operations as well as transportation fuels.

The estimation of greenhouse gas (GHG) emissions from a change in land-use and management resulting from growing biofuel feedstocks has undergone extensive – and often contentious – scientific and policy debate. Emergent renewable fuel policies require life cycle GHG emission accounting that includes biofuel-induced global land-use change (LUC) GHG emissions. However, the science of LUC generally, and biofuels-induced LUC specifically, is nascent and underpinned with great uncertainty.

Land-use change (LUC) is a contentious policy issue because of its uncertain, yet potentially substantial, impact on bioenergy climate change benefits. Currently, the share of global GHG emissions from biofuels-induced LUC is small compared to that from LUC associated with food and feed production and other human-induced causes. However, increasing demand for biofuels derived from feedstocks grown on agricultural land could increase this contribution. No consensus has emerged on how to appropriately isolate and quantify LUC impacts of bioenergy from those of other LUC drivers.

Increasing demand for crop-based biofuels, in addition to other human drivers of land use, induces direct and indirect land use changes (LUC). Our system dynamics tool is intended to complement existing LUC modeling approaches and to improve the understanding of global LUC drivers and dynamics by allowing examination of global LUC under diverse scenarios and varying model assumptions. We report on a small subset of such analyses.