Logging and mill residues are currently the largest sources of woody biomass for bioenergy in the US, but short-rotation woody crops (SRWCs) are expected to become a larger contributor to biomass production, primarily on lands marginal for food production. However, there are very few studies on the environmental effects of SRWCs, and most have been conducted at stand rather than at watershed scales.
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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.
Corn’s (Zea mays L.) stover is a potential nonfood, herbaceous bioenergy feedstock. A vital aspect of utilizing stover for bioenergy production is to establish sustainable harvest criteria that avoid exacerbating soil erosion or degrading soil organic carbon (SOC) levels. Our goal is to empirically estimate the minimum residue return rate required to sustain SOC levels at numerous locations and to identify which macroscale factors affect empirical estimates.
To prepare for a 2014 launch of commercial scale cellulosic ethanol production from corn/maize (Zea mays L.) stover, POET-DSM near Emmetsburg, IA has been working with farmers, researchers, and equipment dealers through “Project Liberty” on harvest, transportation, and storage logistics of corn stover for the past several years. Our objective was to evaluate seven stover harvest strategies within a 50-ha (125 acres) site on very deep, moderately well to poorly drained Mollisols, developed in calcareous glacial till.
Agricultural residues have been identified as a significant potential resource for bioenergy production, but serious questions remain about the sustainability of harvesting residues. Agricultural residues play an important role in limiting soil erosion from wind and water and in maintaining soil organic carbon. Because of this, multiple factors must be considered when assessing sustainable residue harvest limits.
Corn (Zea mays L.) stover is a potential bioenergy feedstock, but little is known about the impacts of reducing stover return on yield and soil quality in the Northern US Corn Belt. Our study objectives were to measure the impact of three stover return rates (Full (~7.8 Mg ha−1 yr−1), Moderate (~3.8 Mg ha−1 yr−1) or Low (~1.5 Mg ha yr−1) Return) on corn and soybean (Glycine max. L [Merr.]) yields and on soil dynamic properties on a chisel-tilled (Chisel) field, and well- (NT1995) or newly- (NT2005) established no-till managed fields.
A global energy crop productivity model that provides geospatially explicit quantitative details on biomass
potential and factors affecting sustainability would be useful, but does not exist now. This study describes a
modeling platform capable of meeting many challenges associated with global-scale agro-ecosystem modeling.
We designed an analytical framework for bioenergy crops consisting of six major components: (i) standardized
natural resources datasets, (ii) global field-trial data and crop management practices, (iii) simulation units and
Net benefits of bioenergy crops, including maize and perennial grasses such as switchgrass, are a function of several factors including the soil organic carbon (SOC) sequestered by these crops. Life cycle assessments (LCA) for bioenergy crops have been conducted using models in which SOC information is usually from the top 30 to 40 cm. Information on the effects of crop management practices on SOC has been limited so LCA models have largely not included any management practice effects.
This paper was presented at the 2012 International Congress on Environmental Modelling and Software in Leipzig, Germany on July 15, 2012.
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.
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.