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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.

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

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.

Author(s):
Tun-Hsiang (Edward) Yu

Supply chain management involves all of the activities in industrial organizations from raw material procurement to final product delivery to customers. The main aim in supply chain management is to satisfy production requirements, while optimizing the economic objectives. In traditional fossil fuel supply chains, huge amounts of fossil fuels are transported via pipelines or tankers with very small costs. These fuels can be transformed into other sources of energy or transportation fuels at their destination points.

Author(s):
Ahu Soylu