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.

Quantifying lignin and carbohydrate composition of corn (Zea mays L.) is important to support the emerging cellulosic biofuels industry. Therefore, field studies with 0 or 100 % stover removal were established in Alabama and South Carolina as part of the Sun Grant Regional Partnership Corn Stover Project. In Alabama, cereal rye (Secale cereale L.) was also included as an additional experimental factor, serving as a winter cover crop.

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.

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

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.

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.

IMPACT – the International Model for Policy Analysis of Agricultural Commodities and Trade – was developed at IFPRI at the beginning of the 1990s, upon the realization that there was a lack of long-term vision and consensus among policy makers and researchers about the actions that are necessary to feed the world in the future, reduce poverty, and protect the natural resource base. In 1993, these same long-term global concerns launched the 2020 Vision for Food, Agriculture and the Environment Initiative.

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.

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.

Growing concern about climate change and energy security has led to increasing interest in developing renewable, domestic energy sources for meeting electricity, heating and fuel needs in the United States. Illinois has significant potential to produce bioenergy crops, including corn, soybeans, miscanthus (Miscanthus giganteus), and switchgrass (Panicum virgatum). However, land requirements for bioenergy crops place them in competition with more traditional agricultural uses, in particular food production.

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.

The Emissions Prediction and Policy Analysis (EPPA) model is the part of the MIT Integrated Global Systems Model (IGSM) that represents the human systems. EPPA is a recursive-dynamic multi-regional general equilibrium model of the world economy, which is built on the GTAP dataset and additional data for the greenhouse gas and urban gas emissions. It is designed to develop projections of economic growth and anthropogenic emissions of greenhouse related gases and aerosols. The main purpose of this report is to provide documentation of a new version of EPPA, EPPA version 4.

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.

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.