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This dataset contains data on agricultural crop and residue production by county in 2041. The agricultural crops in this dataset include barley, corn, cotton, grain sorghum, hay, oats, rice, soybeans, and wheat. The agricultural residues include barley straw, corn stover, oats straw, sorghum stubble, and wheat straw. The dataset was obtained from the database of the BT23 (Davis et al.,2024) for the near-term scenario with biomass market prices of up to $70 per dry ton.

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Organization:
DOE
Author(s):
Jin Wook Ro , Maggie R. Davis , Chad Hellwinckel

This dataset contains data on agricultural crop and residue production by county from 2022 to 2041. The agricultural crop in this dataset includes barley, biomass sorghum, corn, cotton, energy cane, eucalyptus, grain sorghum, hay, miscanthus, oats, pine, poplar, rice, soybean, switchgrass, wheat, and willow, and the agricultural residue includes barley straw, corn stover, oats straw, sorghum stubble, and wheat straw. The dataset was obtained from the database of the BT23 (Davis et al., 2024) for the mature-market medium scenario with biomass market prices of up to $70 per dry ton.

Organization:
DOE
Author(s):
Jin Wook Ro , Maggie R. Davis , Chad Hellwinckel

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

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.

Author(s):
Xiaodong Du

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.

Author(s):
Giovanni Sorda

In 1997, eight E85 (85% ethanol; 15% gasoline) fuel pumps were installed at separate retail fuel stations in Minnesota to provide high-blend ethanol fuel to flexible fuel vehicle (FFV) owners. FFVs capable of utilizing gasoline, E85, or any mixture of the two, were beginning to be mass produced by vehicle manufacturers and distributed through fleet and retail sales nationwide. These state-level E85 efforts were part of larger federal and state policies and programs promoting the use of alternative transportation fuels to displace traditional gasoline and diesel fuel, which continue today.

Author(s):
P. Bromiley

Enhanced environmental quality, fuel security, and economic development along with reduced prices of ethanol-gasoline blends are often used as justifications for the U.S. federal excise tax exemption on ethanol fuels. However, the possible effect of increased overall consumption of fuel in response to lower total price, mitigating the environmental and fuel security benefits, are generally not considered. Taking this price response into account, the optimal U.S. ethanol subsidy is derived.

Author(s):
Dmitry Vedenov