KDF Search Results

This paper analyzes the rural Chinese biomass supply system and models supply chain operations according to U.S. concepts of logistical unit operations: harvest and collection, storage, transportation, preprocessing, and handling and queuing. In this paper, we quantify the logistics cost of corn stover and sweet sorghum in China under different scenarios. We analyze three scenarios of corn stover logistics from northeast China and three scenarios of sweet sorghum stalks logistics from Inner Mongolia in China.

Harvesting of corn stover (plant residues) for cellulosic ethanol production must be balanced with the requirement for returning plant residues to agricultural fields to maintain soil structure, fertility, crop protection, and other ecosystem services. High rates of corn stover removal can be associated with decreased soil organic matter (SOM) quantity and quality and increased highly erodible soil aggregate fractions.

In-field measurements of direct soil greenhouse gas (GHG) emissions provide critical data for quantifying the net energy efficiency and economic feasibility of crop residue-based bioenergy production systems. A major challenge to such assessments has been the paucity of field studies addressing the effects of crop residue removal and associated best practices for soil management (i.e., conservation tillage) on soil emissions of carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4).

Harvesting crop residue needs to be managed to protect agroecosystem health and productivity. DAYCENT, a process-based modeling tool, may be suited to accommodate region-specific factors and provide regional predictions for a broad array of agroecosystem impacts associated with corn stover harvest. Grain yield, soil C, and N2O emission data collected at Corn Stover Regional Partnership experimental sites were used to test DAYCENT performance modeling the impacts of corn stover removal.

The database summarizes a very broad set of old and new standing biomass data from plantation-grown hardwoods and softwoods established under a wide range of conditions across the United States and Canada. The WCYP database, together with this document, is being published to disseminate information on what is available in the literature with respect to yield evaluations and to inform people that not all yield data in the open literature are suitable for evaluation of “potential” regional yields.

This paper describes the current Biomass Scenario Model (BSM) as of August 2013, a system dynamics model developed under the support of the U.S. Department of Energy (DOE). The model is the result of a multi-year project at the National Renewable Energy Laboratory (NREL). It is a tool designed to better understand biofuels policy as it impacts the development of the supply chain for biofuels in the United States.

A woody crop yield potential (WCYP) database was created containing yield results with as much associated information as was available concerning the sites, soils, and experimental treatments. The database summarizes a very broad set of old and new standing biomass data from plantation-grown hardwoods and softwoods established under a wide range of conditions across the United States and Canada.

Corn stover is targeted as a potential non-food bioenergy feedstock, especially in the Midwest United States.  Three parallel experiments on adjacent fields, one is managed without tillage since 1995, a second experiment is managed without tillage since 2005, and the third is managed with chisel plowing since 2005.  The residue removal treatments are the same in all experiments, with 0, 50%, 75% and 100% of the rows from plots in the corn phase of the rotation harvested. In 2008, the 75% stover removal was changed to cob removal.

Nationwide spatial dataset representing the polygon areas for first-generation suitability analysis of potentially suitable areas for microalgae open ponds. The PNNL microalgae growth model results for each site are included in the attribute table and assume growth based on theoretical limits. Sites represent a minimum mapping unit of 490 hectares. Land suitability included area less than or equal to 1% slope on non-agricultural, undeveloped or low‐density developed, nonsensitive, generally noncompetitive land was considered for microalgal culture facilities.

Microalgae are receiving increased global attention as a potential sustainable “energy crop”for biofuel production. An important step to realizing the potential of algae is quantifying the demands commercial‐scale algal biofuel production will place on water and land resources. We present a high‐resolution spatiotemporal assessment that brings to bear fundamental questions of where production can occur, how many land and water resources are required, and how much energy is produced.

We quantify the emergence of biofuel markets and its impact on U.S. and world agriculture for the coming decade using the multi-market, multi-commodity international FAPRI (Food and Agricultural Policy Research Institute) model. The model incorporates the trade-offs between biofuel, feed, and food production and consumption and international feedback effects of the emergence through world commodity prices and trade.

The Center for Sustainability and the Global Environment (SAGE) at the University of Wisconsin has been developing global databases of contemporary and historical agricultural land use and land cover. SAGE has chosen to focus on agriculture because it is clearly the predominant land use activity on the planet today, and provides a vital service?i.e., food?for human societies. SAGE has developed a ?data fusion?

The preceding two chapters of this volume have discussed physical and economic data bases for global agriculture and forestry, respectively. These form the foundation for the integrated, global land use data base discussed in this chapter. However, in order to utilize these data for global CGE analysis, it is first necessary to integrate them into a global, general equilibrium data base. This integration is the subject of the present chapter

This study presents the results of comparing land use estimates between three different data sets for the Upper Mississippi River Basin (UMRB). The comparisons were performed between the U.S. Department of Agriculture (USDA) Natural Resource Conservation Service (NRCS) National Resource Inventory (NRI), the U.S. Geological Survey (USGS) National Land Cover Data (NLCD) database, and a combined USDA National Agricultural Statistics Service (NASS) Agricultural Census – NLCD dataset created to support applications of the Hydrologic Unit Model for the U.S. (HUMUS).

This paper presents a range of future, spatially explicit, land use change scenarios for the EU15, Norway and Switzerland based on an interpretation of the global storylines of the Intergovernmental Panel on Climate Change (IPCC) that are presented in the special report on emissions scenarios (SRES). The methodology is based on a qualitative interpretation of the SRES storylines for the European region, an estimation of the aggregate totals of land use change using various land use change models and the allocation of these aggregate quantities in space using spatially explicit rules.

Discussions of alternative fuel and propulsion technologies for transportation often overlook the infrastructure required to make these options practical and cost-effective. We estimate ethanol production facility locations and use a linear optimization model to consider the economic costs of distributing various ethanol fuel blends to all metropolitan areas in the United States. Fuel options include corn-based E5 (5% ethanol, 95% gasoline) to E16 from corn and switchgrass, as short-term substitutes for petroleum-based fuel.

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution.

Land use change models are tools to support the analysis of the causes and consequences of land use dynamics. Scenario analysis with land use models can support land use planning and policy. Numerous land use models are available, developed from different disciplinary backgrounds. This paper reviews current models to identify priority issues for future land use change modelling research.

The U.S. Departments of Agriculture and Energy jointly analyzed the economic potential for, and impacts of, large-scale bioenergy crop production in the United States. An agricultural sector model (POLYSYS) was modified to include three potential bioenergy crops (switchgrass, hybrid poplar, and willow). At farmgate prices of US $2.44/GJ, an estimated 17 million hectares of bioenergy crops, annually yielding 171 million dry Mg of biomass, could potentially be produced at a profit greater than existing agricultural uses for the land.