Supplementary spatial data for Available Land for Cellulosic Biofuel Production: A Supply Chain Centered Comparison

O'Neill, Eric; Lark, Tyler; Xie, Yanhua; Basso, Bruno
Issue date: 28 July 2023
Cite as:
O'Neill, Eric, Lark, Tyler, Xie, Yanhua, & Basso, Bruno. (2023). Supplementary spatial data for Available Land for Cellulosic Biofuel Production: A Supply Chain Centered Comparison [Data set]. Princeton University. https://doi.org/10.34770/dkc7-ws77
@electronic{oneill_eric_2023,
  author      = {O'Neill, Eric and
                Lark, Tyler and
                Xie, Yanhua and
                Basso, Bruno},
  title       = {{Supplementary spatial data for Available
                 Land for Cellulosic Biofuel Production:
                 A Supply Chain Centered Comparison}},
  publisher   = {{Princeton University}},
  year        = 2023,
  url         = {https://doi.org/10.34770/dkc7-ws77}
}
Abstract:

Collection of the underlying spatially explicit data for Available Land for Cellulosic Biofuel Production: A Supply Chain Centered Comparison. Includes raw biomass yield data and soil carbon sequestration potential data for three types of marginal land for the USA midwest at the field level including field areas. Collection also includes raw land rasters for the three types of marginal land, model parameters for the MILP model used in the study, and results used to generate the figures in the paper.

Show More
Description:

This dataset is too large to download directly from this item page. You can access and download the data via Globus at this link: https://app.globus.org/file-manager?destination_id=dc43f461-0ca7-4203-848c-33a9fc00a464&destination_path=%2Fdkc7-ws77%2F (See https://docs.globus.org/how-to/get-started/ for instructions on how to use Globus; sign-in is required).

Show More
More about this record
Authors O'Neill, Eric
Lark, Tyler
Xie, Yanhua
Basso, Bruno
Contributors Kim, Seungdo, Robertson, Phillip, Dale, Bruce, Maravelias, Christos
Communities Chemical and Biological Engineering
Collection Tags Research Data Sets
Date Accessioned 28 July 2023
Issue date 28 July 2023
Date Created 14 July 2023
URI http://arks.princeton.edu/ark:/88435/dsp01hx11xj530
URI https://doi.org/10.34770/dkc7-ws77
URI https://app.globus.org/file-manager?destination_id=dc43f461-0ca7-4203-848c-33a9fc00a464&destination_path=%2Fdkc7-ws77%2F
Table of Contents /ONEILL_SPATIALDATASET_README.txt /BiomassData - yieldSOCdata.db: The yield, soil carbon sequestration, field area, and locations for fields identified marginal land and with crop growth simulated using the SALUS biogeochemical crop model. /LandRasters -/LandRasters/HAL: Geographically referenced .tif files for field-specific bioenergy land identified as historically abandoned -/LandRasters/RAL: Geographically referenced .tif files for field-specific bioenergy land identified as recently abandoned - https://doi.org/10.5281/zenodo.3905242 gives detail for the entire conterminous USA, RAL includes just the lands identified as expanded, intermittent, or abandoned between 2008 and 2016 as described in the referenced DOI. Unlike the referenced DOI, RAL includes only the USA midwest at 30m resolution. -/LandRasters/LCL: Geographically referenced .tif files for field-specific bioenergy land identified as low capability land /ModelParameters -ParametersWithSources.xlsx: Economic, environmental, efficiency parameters used to parametrize the MILP model used in the study -PotentialLocations.xlsx: Latitude and longitude coordinates for potential biorefinery and preprocessing depot locations -Individual .csv files contain the parameters indicated by the file title, the units, and sources. content is the same as the .xlsx files. -/ModelParameters/RefineryParameters.csv -/ModelParameters/DepotParameters.csv -/ModelParameters/TranportationParameters.csv -/ModelParameters/InventoryParameters.csv -/ModelParameters/LandscapeParameters.csv -/ModelParameters/SourcesSummary.csv -/ModelParameters/PotentialDepotLocations.csv -/ModelParameters/PotentialRefineryLocation.csv /PlotData -DemandInstances.csv: The results of system optimization used to generate figures in the above paper -epsilonInstances.csv: The results of system optimization used to generate figures in the above paper
Language en_US
Publisher Princeton University
Rights This work is licensed under CC BY 4.0. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Type Dataset
Spatial Coverage USA Midwest states: MI, OH, IN, IL, WI, IA, MO, MN
Temporal Coverage yieldSOCdata.db start=1981;end=2019
Show More