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.

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.

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

The harvest of corn stover or herbaceous crops as feedstocks for bioenergy purposes has been shown to have significant benefits from energy and climate change perspectives. There is a potential, however, to adversely impact water and soil quality, especially in Midwestern states where the biomass feedstock production would predominantly occur.

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).

National interests in greater energy independence, concurrent with favorable market forces, have driven increased production of corn-based ethanol in the United States and research into the next generation of biofuels. The trend is changing the national agricultural landscape and has raised concerns about potential impacts on the nation?s water resources. This report examines some of the key issues and identifies opportunities for shaping policies that help to protect water resources.

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.

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.

Power generation emits significant amounts of greenhouse gases (GHGs), mainly carbon dioxide (CO2). Sequestering CO2 from the power plant flue gas can significantly reduce the GHGs from the power plant itself, but this is not the total picture. CO2 capture and sequestration consumes additional energy, thus lowering the plant's fuel-to-electricity efficiency. To compensate for this, more fossil fuel must be procured and consumed to make up for lost capacity.

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.

Land-use change models are used by researchers and professionals to explore the dynamics and drivers of land-use/land-cover change and to inform policies affecting such change. A broad array of models and modeling methods are available to researchers, and each type has certain advantages and disadvantages depending on the objective of the research. This report presents a review of different types of models as a means of exploring the functionality and ability of different approaches.

This paper presents an overview of multi-agent system models of land-use/cover change (MAS/LUCC models). This special class of LUCC models combines a cellular landscape model with agent-based representations of decisionmaking, integrating the two components through specification of interdependencies and feedbacks between agents and their environment. The authors review alternative LUCC modeling techniques and discuss the ways in which MAS/LUCC models may overcome some important limitations of existing techniques. We briefly review ongoing MAS/LUCC modeling efforts in four research areas.

Biomass is a significant contributor to the US economy--agriculture, forest and paper products, food and related products account for 5% of our GDP. While the forest products industry self generates some of their energy, other sectors are importers. Bioenergy can contribute to economic development and to the environment. Examples of bioenergy routes suggest that atmospheric carbon can be cycled through biofuels in carefully designed systems for sustainability. Significant potential exists for these options.

We present a system dynamics global LUC model intended to examine LUC attributed to biofuel production. The model has major global land system stocks and flows and can be exercised under different food and biofuel demand assumptions. This model provides insights into the drivers and dynamic interactions of LUC, population, dietary choices, and biofuel policy rather than a precise number generator.