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.
We quantify the emergence of biofuel markets and its impact on U.S. and world agriculture for the coming decade using the multi-market, multi-commodity international FAPRI (Food and Agricultural Policy Research Institute) model. The model incorporates the trade-offs between biofuel, feed, and food production and consumption and international feedback effects of the emergence through world commodity prices and trade.
Land-use changes are frequently indicated to be one of the main human-induced factors influencing the groundwater system. For land-use change, groundwater research has mainly focused on the change in water quality thereby neglecting changes in quantity. The objective of this paper is to assess the impact of land-use changes, from 2000 until 2020, on the hydrological balance and in particular on groundwater quantity, as results from a case study in the Kleine Nete basin, Belgium.
In this paper we investigate the potential production and implications of a global biofuels industry. We develop alternative approaches to the introduction of land as an economic factor input, in value and physical terms, into a computable general equilibrium framework. Both approach allows us to parameterize biomass production in a manner consistent with agro-engineering information on yields and a ?second generation? cellulosic biomass conversion technology.
Agricultural activities have dramatically altered our planet?s land surface. To understand the extent and spatial distribution of these changes, we have developed a new global data set of croplands and pastures circa 2000 by combining agricultural inventory data and satellite-derived land cover data. The agricultural inventory data, with much greater spatial detail than previously available, is used to train a land cover classification data set obtained by merging two different satellite-derived products (Boston University?s MODIS-derived land cover product and the GLC2000 data set).
Growing concern about climate change and energy security has led to increasing interest in developing renewable, domestic energy sources for meeting electricity, heating and fuel needs in the United States. Illinois has significant potential to produce bioenergy crops, including corn, soybeans, miscanthus (Miscanthus giganteus), and switchgrass (Panicum virgatum). However, land requirements for bioenergy crops place them in competition with more traditional agricultural uses, in particular food production.
Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution.
Human actions are altering the terrestrial environment at unprecedented rates, magnitudes, and spatial scales. Landcover change stemming from human land uses represents a major source and a major element of global environmental change. Not only are the global-level data on landuse and land-cover change relatively poor, but we need a much better understanding of the underlying driving forces for these changes. Many forces have been proposed as significant, but single-factor explanations of land transformation have proved to be inadequate.
In 2013 a series of meetings was held across the US with each of the Sun Grant Regional Feedstock Partnership crop teams and the resource assessment team, led by the Oregon State University and Oak Ridge National Laboratory, to review, standardize, and verify energy crop yield trials from 2007-2012 and assimilate their outcomes into a national model of biomass yield suitability.
This document provides presentation style maps of potential crop yield of dedicated bioenergy crops from the publication "Productivity Potential of Bioenergy Crops from the Sun Grant Regional Feedstock Partnership." 2013. Eaton, Laurence, Chris Daly, Mike Halbleib, Vance Owens, Bryce Stokes. ORNL/TM-2013/574.
Switchgrass (Panicum virgatum L.) is a perennial grass native to the United States that has been studied as a sustainable source of biomass fuel. Although many field-scale studies have examined the potential of this grass as a bioenergy crop, these studies have not been integrated. In this study, we present an empirical model for switchgrass yield and use this model to predict yield for the conterminous United States. We added environmental covariates to assembled yield data from field trials based on geographic location. We developed empirical models based on these data.
Traffic flows in the U.S. have been affected by the substantial increase and, as of January 2009, decrease in biofuel production and use. This paper considers a framework to study the effect on grain transportation flows of the 2005 Energy Act and subsequent legislation, which mandated higher production levels of biofuels, e.g. ethanol and biodiesels. Future research will incorporate changes due to the recent economic slowdown.
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.
FAOSTAT provides time-series and cross sectional data relating to food and agriculture for some 200 countries.
The national version of FAOSTAT, CountrySTAT, is being developed and implemented in a number of target countries, primarily in sub-saharan Africa. It will offer a two-way data exchange facility between countries and FAO as well as a facility to store data at the national and sub-national levels.
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.
One of the major objectives of the current expansion in bioenergy cropping is to reduce global greenhouse gas emissions for environmental benefit. The cultivation of bioenergy and biofuel crops also affects biodiversity more directly, both positively and negatively.
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.
Use the Alternative Fuels Data Center (AFDC) station locator to find hydrogen fuel stations across the U.S.
Use the Alternative Fuels Data Center (AFDC) station locator to find compressed natural gas stations across the U.S.