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Title: NREL Biomethane GIS Data

This dataset contains information about the biomass resources generated by county in the United States. It includes the following feedstock categories: crop residues, forest residues, primary mill residues, secondary mill residues, and urban wood waste. The estimates are based on county-level statistics and/or point-source data gathered from the U.S. Department of Agriculture (USDA), USDA Forest Service, EPA and other organizations, which are further processed using relevant assumptions and conversions.
Authors:
Publication Date:
Report Number(s):
44
DOE Contract Number:
GO28308
Product Type:
Dataset
Research Org(s):
National Renewable Energy Laboratory - Data (NREL-DATA), Golden, CO (United States); National Renewable Energy Laboratory
Collaborations:
National Renewable Energy Laboratory
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Fuel Cell Technologies Office (EE-3F)
Subject:
09 BIOMASS FUELS; 47 OTHER INSTRUMENTATION; 96 KNOWLEDGE MANAGEMENT AND PRESERVATION; NREL; energy; data; Biomass; GIS; biomethane; shapefile; renewable energy; RE; United States; geospatial
OSTI Identifier:
1258437

Milbrandt, Anelia. NREL Biomethane GIS Data. United States: N. p., Web. doi:10.7799/1258437.
Milbrandt, Anelia. NREL Biomethane GIS Data. United States. doi:10.7799/1258437.
Milbrandt, Anelia. 2016. "NREL Biomethane GIS Data". United States. doi:10.7799/1258437. https://www.osti.gov/servlets/purl/1258437.
@misc{osti_1258437,
title = {NREL Biomethane GIS Data},
author = {Milbrandt, Anelia},
abstractNote = {This dataset contains information about the biomass resources generated by county in the United States. It includes the following feedstock categories: crop residues, forest residues, primary mill residues, secondary mill residues, and urban wood waste. The estimates are based on county-level statistics and/or point-source data gathered from the U.S. Department of Agriculture (USDA), USDA Forest Service, EPA and other organizations, which are further processed using relevant assumptions and conversions.},
doi = {10.7799/1258437},
year = {2016},
month = {6} }
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