Link to the website with documentation and download instructions for the PNNL Global Change Assessment Model (GCAM), a community model or long-term, global energy, agriculture, land use, and emissions. BioEnergy production, transformation, and use is an integral part of GCAM modeling and scenarios.
The compatibility of elastomeric materials used in fuel storage and dispensing applications was determined for test fuels
representing neat gasoline and gasoline blends containing 10 and 17 vol.% ethanol, and 16 and 24 vol.% isobutanol. The
actual test fuel chemistries were based on the aggressive formulations described in SAE J1681 for oxygenated gasoline.
Elastomer specimens of fluorocarbon, fluorosilicone, acrylonitrile rubber (NBR), polyurethane, neoprene, styrene
The compatibility of plastic materials used in fuel storage and dispensing applications was determined for test fuels representing gasoline blended with 25 vol.% ethanol and gasoline blended with 16 and 24 vol.% isobutanol. Plastic materials included those used in flexible plastic piping and fiberglass resins. Other commonly used plastic materials were also evaluated. The plastic specimens were exposed to Fuel C, CE25a, CiBu16a, and CiBu24a for 16 weeks at 60oC.
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
This article summarises the compatibility of six elastomers – used in fuel
storage and delivery systems – with test fuels representing gasoline blended
with up to 85% ethanol. Individual coupons were exposed to test fuels for four
weeks to achieve saturation. The change in volume and hardness, when wetted
and after drying, were measured and compared with the original condition.
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.
In response to concerns about oil dependency and the contributions of fossil fuel use to climatic change, the U.S. Department of Energy has begun a research initiative to make 20% of motor fuels biofuel based in 10 years, and make 30% of fuels bio-based by 2030. Fundamental to this objective is developing an understanding of feedstock dynamics of crops suitable for cellulosic ethanol production. This report focuses on switchgrass, reviewing the existing literature from field trials across the United States, and compiling it for the first time into a single database.
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 presentation summarizes findings of a life cycle analysis of the energy and environmental impacts of converting corn stove (the residue from corn harvesting) to ethanol.
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.