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Price Scenarios at $54 and $119 were simulated for Switchgrass, Miscanthus and Willow production from 2017 to 2040. These analyses were used in Woodbury, Peter B., et al. 2018. "Improving water quality in the Chesapeake Bay using payments for ecosystem services for perennial biomass for bioenergy and biofuel production." Biomass and Bioenergy 114:132-142. doi: https://doi.org/10.1016/j.biombioe.2017.01.024.

Organization:
USDA
Author(s):
Maggie R. Davis

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
 
 
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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.

Biomass Scenario Model: Supplemental Tableau workbook for Christopher M Clark et al 2013 Environ. Res. Lett. 8 025016 doi:10.1088/1748-9326/8/2/025016 Growing a sustainable biofuels industry: economics, environmental considerations, and the role of the Conservation Reserve Program

To explore this file download Tableau reader: http://www.tableausoftware.com/products/reader

This paper describes the current Biomass Scenario Model (BSM) as of August 2013, a system dynamics model developed under the support of the U.S. Department of Energy (DOE). The model is the result of a multi-year project at the National Renewable Energy Laboratory (NREL). It is a tool designed to better understand biofuels policy as it impacts the development of the supply chain for biofuels in the United States.

Author(s):
Peterson, Steve

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.

ABSTRACT. Adding bioenergy to the U.S. energy portfolio requires long‐term profitability for bioenergy producers and long‐term protection of affected ecosystems. In this study, we present steps along the path toward evaluating both sides of the sustainability equation (production and environmental) for switchgrass (Panicum virgatum) using the Soil and Water Assessment Tool (SWAT). We modeled production of switchgrass and river flow using SWAT for current landscapes at a regional scale.

Author(s):
Latha Baskaran

Transitioning to a larger biofuels industry requires a robust biomass-to-biofuels system of systems that operates within existing agriculture, forestry, energy, and transportation markets. Using the existing fuel supply chain infrastructure as a framework, this paper discusses a vision for biomass-based fuels and the challenges associated with a massive market and infrastructure transformation.

Author(s):
Riley, Cynthia J. , Sandor, Debra
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

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.

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.

The most frequently used climate classification map is that ofWladimir Köppen, presented in its latest version
1961 by Rudolf Geiger. A huge number of climate studies and subsequent publications adopted this or a
former release of the Köppen-Geiger map. While the climate classification concept has been widely applied
to a broad range of topics in climate and climate change research as well as in physical geography, hydrology,
agriculture, biology and educational aspects, a well-documented update of the world climate classification

Author(s):
Dr. Markus Kottek

In a previous paper we presented an update of the highly referenced climate classification map, that of Wladimir Koppen, which was published for the first time in 1900 and updated in its latest version by Rudolf Geiger in 1961. This updated world map of Koppen-Geiger climate classification was based on temperature and precipitation observations for the period 1951–2000.

Author(s):
Dr. Franz Rubel