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This dataset was utilized in a report to highlight parameters that affect near-term sustainable supply of corn stover and forest resources at $56 and $74 per dry ton delivered. While the report focus is restricted to 2018, the modeling runs are available from 2016-2022. In the 2016 Billion-ton Report (BT16), two stover cases were presented. In this dataset, we vary technical levels of those assumptions to measure stover supply response and to evaluate the major determinants of stover supply.

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

This spreadsheet serves as an Input file to the National Renewable Energy Laboratory's Waste-to-Energy System Simulation (WESyS) model developed in Stella Pro (isee systems, Lebanon, NH). WESyS is a national-level system dynamics model that simulates energy production from three sectors of the U.S. waste-to-energy industry: landfills, confined animal feeding operations (CAFOs), and publically owned treatment works (POTWs).

Author(s):
Daniel Inman, Annika Eberle, and Dylan Hettinger of the National Renewable Energy Laboratory; Steven Peterson and Corey Peck of Lexidyne, LLC.
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

This spreadsheet serves as an Input file to the National Renewable Energy Laboratory's Waste-to-Energy System Simulation (WESyS) model developed in Stella Pro (isee systems, Lebanon, NH). WESyS is a national-level system dynamics model that simulates energy production from three sectors of the U.S. waste-to-energy industry: landfills, confined animal feeding operations (CAFOs), and publically owned treatment works (POTWs).

Author(s):
Daniel Inman, Annika Eberle, and Dylan Hettinger of the National Renewable Energy Laboratory; Steven Peterson and Corey Peck of Lexidyne, LLC.
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

This spreadsheet serves as an Input file to the National Renewable Energy Laboratory's Waste-to-Energy System Simulation (WESyS) model developed in Stella Pro (isee systems, Lebanon, NH). WESyS is a national-level system dynamics model that simulates energy production from three sectors of the U.S. waste-to-energy industry: landfills, confined animal feeding operations (CAFOs), and publically owned treatment works (POTWs).

Author(s):
Daniel Inman, Annika Eberle, and Dylan Hettinger of the National Renewable Energy Laboratory; Steven Peterson and Corey Peck of Lexidyne, LLC.
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

Waste to Energy System Simulation Model (WESyS) - Scenario Inputs and Supplemental Tableau Workbook
Daniel Inman, Ethan Warner, Anelia Milbrandt, Alberta Carpenter, Ling Tao, Emily Newes, and Steve Peterson (Lexidyne, LLC)

Author(s):
Daniel Inman, Ethan Warner, Anelia Milbrandt, Alberta Carpenter, Ling Tao, Emily Newes, and Steve Peterson (Lexidyne, LLC)
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

A framework for selecting and evaluating indicators of bioenergy sustainability is presented.
This framework is designed to facilitate decision-making about which indicators are useful for assessing
sustainability of bioenergy systems and supporting their deployment. Efforts to develop sustainability
indicators in the United States and Europe are reviewed. The fi rst steps of the framework for
indicator selection are defi ning the sustainability goals and other goals for a bioenergy project or program,

Author(s):
Virginia Dale
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

Vimmerstedt, L. J., Bush, B. W., Hsu, D. D., Inman, D. and Peterson, S. O. (2014), Maturation of biomass-to-biofuels conversion technology pathways for rapid expansion of biofuels production: a system dynamics perspective. Biofuels, Bioprod. Bioref.. doi: 10.1002/bbb.1515
 
 
To explore this file download Tableau reader: http://www.tableausoftware.com/products/reader

Author(s):
NREL

Understanding the development of the biofuels industry in the United States is important to policymakers and industry. The Biomass Scenario Model (BSM) is a system dynamics model of the biomass-to-biofuels system that can be used to explore policy effects on biofuels development. Because of the complexity of the model, as well as the wide range of possible future conditions that affect biofuels industry development, we have not developed a single reference case but instead developed a set of specific scenarios that provide various contexts for our analyses.

Author(s):
Inman, D.; Vimmerstedt, L.; Bush, B.; Peterson, S.
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

The Biomass Scenario Model (BSM) is a system dynamics model that represents the entire biomass-to-biofuels supply chain, from feedstock to fuel use. The BSM is a complex model that has been used for extensive analyses; the model and its results can be better understood if input data used for initialization and calibration are well-characterized. It has been carefully validated and calibrated against the available data, with data gaps filled in using expert opinion and internally consistent assumed values.

Author(s):
Lin, Y. ; , Newes, E. , Bush, B. , Peterson, S. , Stright, D.
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

In support of the national goals for biofuel use in the United States, numerous technologies have been developed that convert biomass to biofuels. Some of these biomass to biofuel conversion technology pathways are operating at commercial scales, while others are in earlier stages of development. The advancement of a new pathway toward commercialization involves various types of progress, including yield improvements, process engineering, and financial performance.

Author(s):
Laura J. Vimmerstedt , Brian W. Bush
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

The Biomass Energy Data Book is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the Biomass Program in the Energy Efficiency and Renewable Energy (EERE) program of the Department of Energy (DOE). Designed for use as a convenient reference, the book represents an assembly and display of statistics and information that characterize the biomass industry, from the production of biomass feedstocks to their end use, including discussions on sustainability.

Author(s):
Robert Boundy , Susan W. Diegel , Lynn Wright , Stacy C. Davis
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

The production of biobased feedstocks (i.e., plant– or algal-based material use for transportation fuels, heat, power and bioproducts) for energy consumption has been expanding rapidly in recent years. Biomass now accounts for 4.1% of total U.S. primary energy production. Unfortunately, there are considerable knowledge gaps relative to implications of this industry expansion for wildlife.

Author(s):
Rupp, S. P., L. Bies, A. Glaser, C. Kowaleski, T. McCoy, T. Rentz, S. Riffell, J. Sibbing, J. Verschuyl, and T. Wigley.

Biomass Scenario Model Zotero References
National Renewable Energy Laboratory

Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

We present a system dynamics global LUC model intended to examine LUC attributed to biofuel production. The model has major global land system stocks and flows and can be exercised under different food and biofuel demand assumptions. This model provides insights into the drivers and dynamic interactions of LUC, population, dietary choices, and biofuel policy rather than a precise number generator.