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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.

Vimmerstedt, L. J., Bush, B. W., Hsu, D. D., Inman, D. and Peterson, S. O. (2014), Maturation of biomass-to-biofuels conversion technology pathways for rapid expansion of biofuels production: a system dynamics perspective. Biofuels, Bioprod. Bioref.. doi: 10.1002/bbb.1515
 
 
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In support of the national goals for biofuel use in the United States, numerous technologies have been developed that convert biomass to biofuels. Some of these biomass to biofuel conversion technology pathways are operating at commercial scales, while others are in earlier stages of development. The advancement of a new pathway toward commercialization involves various types of progress, including yield improvements, process engineering, and financial performance.

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).

Biomass is receiving increasing attention as scientists, policy makers, and growers search for clean, renewable energy alternatives. Compared with other renewable resources, biomass is very flexible it can be used as fuel for direct combustion, gasified, used in combined heat and power technologies, or biochemical conversions. Due to the wide range of feedstocks, biomass has a broad geographic distribution, in some cases offering a least-cost and near-term alternative. The objective of this research is to estimate the biomass resources available in the United States and map the results.

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.

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).

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.

The US is currently the world's largest ethanol producer. An increasing percentage is used as transportation fuel, but debates continue on its costs competitiveness and energy balance. In this study, technological development of ethanol production and resulting cost reductions are investigated by using the experience curve approach, scrutinizing costs of dry grind ethanol production over the timeframe 1980–2005. Cost reductions are differentiated between feedstock (corn) production and industrial (ethanol) processing.

A dry-grind ethanol from corn process analysis is performed. After defining a complete model of the process, a pinch technology analysis is carried out to optimise energy and water demands. The so-defined base case is then discussed in terms of production costs and process profitability. A detailed sensitivity analysis on the most important process and financial variables is carried out. The possibility to adopt different alternatives for heat and power generation combined to the process is evaluated.

Production costs of bio-ethanol from sugarcane in Brazil have declined continuously over the last three decades. The aims of this study are to determine underlying reasons behind these cost reductions, and to assess whether the experience curve concept can be used to describe the development of feedstock costs and industrial production costs. The analysis was performed using average national costs data, a number of prices (as a proxy for production costs) and data on annual Brazilian production volumes.

The important key technologies required for the successful biological conversion of lignocellulosic biomass to ethanol have been extensively reviewed. The biological process of ethanol fuel production utilizing lignocellulose as substrate requires: (1) delignification to liberate cellulose and hemicellulose from their complex with lignin, (2) depolymerization of the carbohydrate polymers (cellulose and hemicellulose) to produce free sugars, and (3) fermentation of mixed hexose and pentose sugars to produce ethanol.

The U.S. Geological Survey (USGS) 2001 National Land Cover Database (NLCD) was compared to the U.S. Department of Agriculture (USDA) 2002 Census of Agriculture. Wecompared areal estimates for cropland at the state and county level for 14 States in the Upper Midwest region of the United States. Absolute differences between the NLCD and Census cropland areal estimates at the state level ranged from 1.3% (Minnesota) to 37.0% (Wisconsin). The majority of counties (74.5%) had differences of less than 100 km2. 7.2% of the counties had differences of more than 200 km2.

Ground-based data on crop production in the USA is provided through surveys conducted by the National Agricultural Statistics Service (NASS) and the Census of Agriculture (AgCensus). Statistics from these surveys are widely used in economic analyses, policy design, and for other purposes. However, missing data in the surveys presents limitations for research that requires comprehensive data for spatial analyses.We created comprehensive county-level databases for nine major crops of the USA for a 16-yr period, by filling the gaps in existing data reported by NASS and AgCensus.