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The Biomass Scenario Model (BSM) is a system dynamics model that represents the entire biomass-to-biofuels supply chain, from feedstock to fuel use. 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.

This page houses the BSM articles that have been published. For more information, see the link to NREL's list of publications on the BSM.

There is an inextricable link between energy production and food/feed/fiber cultivation with available water resources. Currently in the United States, agriculture represents the largest sector of consumptivewater usemaking up 80.7%of the total. Electricity generation in the U.S. is projected to increase by 24 % in the next two decades and globally, the production of liquid transportation fuels are forecasted to triple over the next 25-years, having significant impacts on the import/export market and global economies.

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

The Biomass Program is one of the nine technology development programs within the Office of Energy Efficiency and Renewable Energy (EERE) at the U.S. Department of Energy (DOE). This 2011 Multi-Year Program Plan (MYPP) sets forth the goals and structure of the Biomass Program. It identifies the research, development, demonstration, and deployment (RDD&D) activities the Program will focus on over the next five years, and outlines why these activities are important to meeting the energy and sustainability challenges facing the nation.

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

This model was developed at Idaho National Laboratory and focuses on crop production. This model is an agricultural cultivation and production model, but can be used to estimate biomass crop yields.

Author(s):
Hoskinson, R.L.

Estimates of vehicle miles traveled (VMT) are used extensively in transportation planning for allocating resources, estimating vehicle emissions, computing energy consumption, and assessing traffic impact. The estimates used in these applications usually come from different sources. For an objective comparison of VMT estimates from different methods, the principles and assumptions supporting the methods and the potential sources of error associated with the methods must be clearly understood.

Author(s):
Robert K. Kumapley

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.

Crop intensification is often thought to increase greenhouse gas (GHG) emissions, but studies in which crop management is optimized to exploit crop yield potential are rare. We conducted a field study in eastern Nebraska, USA to quantify GHG emissions, changes in soil organic carbon (SOC) and the net global warming potential (GWP) in four irrigated systems: continuous maize with recommended best management practices (CC-rec) or intensive management (CC-int) and maize–soybean rotation with recommended (CS-rec) or intensive management (CS-int).

USDA Agricultural Projections for 2011-20, released in February 2011, provide longrun projections for the farm sector for the next 10 years. These annual projections cover agricultural commodities, agricultural trade, and aggregate indicators of the sector, such as farm income and food prices.

Important assumptions for the projections include:

Author(s):
USDA Economic Research Service

PEATSim (Partial Equilibrium Agricultural Trade Simulation) is a dynamic, partial equilibrium, mathematical-based model that enables users to reach analytical solutions to problems, given a set of parameters, data, and initial
conditions. This theoretical tool developed by ERS incorporates a wide range of domestic and border policies that enables it to estimate the market and trade effects of policy changes on agricultural markets. PEATSim captures

Author(s):
USDA Economic Research Service

Agricultural markets often feature significant transport costs and spatially distributed production and processing which causes spatial imperfect competition. Spatial economics considers the firms’ decisions regarding location and spatial price strategy separately, usually on the demand side, and under restrictive assumptions. Therefore, alternative approaches are needed to explain, e.g., the location of new ethanol plants in the U.S. at peripheral as well as at central locations and the observation of different spatial price strategies in the market.

Author(s):
Graubner, Marten

This database contains current and historical official USDA data on production, supply and distribution of agricultural commodities for the United States and key producing and consuming countries.

Author(s):
USDA Foreign Agriculture Service

In the corn ethanol industry, the ability of plants to obtain favorable prices through marketing decisions is considered important for their overall economic performance. Based on a panel of surveyed of ethanol plants we extend data envelopment analysis (DEA) to decompose the economic efficiency of plants into conventional sources (technical and allocative efficiency) and a new component we call marketing efficiency.

Author(s):
Sesmero, Juan S.

The National Renewable Energy Laboratory (NREL) originally developed this application for biopower with funding from the Environmental Protection Agency's Blue Skyways Collaborative. The Department of Energy's Office of Biomass Program provided funding for biofuels functionality. More information on funding agencies is available: http://www.blueskyways.org and http://www.eere.energy.gov/biomass/.

Use the Alternative Fuels Data Center (AFDC) station locator to find LNG stations across the U.S.

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

Use the Alternative Fuels Data Center (AFDC) station locator to find hydrogen fuel stations across the U.S.

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

Use the Alternative Fuels Data Center (AFDC) station locator to find compressed natural gas stations across the U.S.

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

Use the Alternative Fuels Data Center (AFDC) station locator to find electric fuel stations across the U.S.

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

Search for and download detailed data on fueling stations for several different types of alternative fuels.

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