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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.

ORNL Report ORNL/TM-2010-120.

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.

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.

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.

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.

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.

Biofuels are presented in rich countries as a solution to two crises: the climate crisis and the oil crisis. But they may not be a solution to either, and instead are contributing to a third: the current food crisis.

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).

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.

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:

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

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.

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.

This study quantifies the impact of increasing ethanol production on wholesale/retail gasoline prices employing pooled regional time-series data from January 1995 to March 2008. We find that the growth in ethanol production kept wholesale gasoline prices $0.14/gallon lower than would otherwise have been the case. The negative impact of ethanol on retail gasoline prices is found to vary considerably across regions. The Midwest region has the biggest impact at $0.28/gallon, while the Rocky Mountain region had the smallest impact at $0.07/gallon.

In the last decade biofuel production has been driven by governmental policies. This article reviews the national strategy plans of the world’s leading producers. Particular attention is dedicated to blending targets, support schemes and feedstock use. Individual country profiles are grouped by continent and include North America (Canada and the US), South America (Argentina, Brazil, and Colombia), Europe (the European Union, France, and Germany), Asia (China, India, Indonesia, Malaysia, and Thailand) and Australia.

The rapidly expanding biofuel industry has changed the fundamentals of U.S. agricultural commodity markets. Increasing ethanol and biodiesel production has generated a fast-growing demand for corn and soybean products, which competes with the well-established domestic livestock industry and foreign buyers. Meanwhile, the co-products of biofuel production are replacing or displacing coarse grains and oilseed meal in feed rations for livestock.