This project looks at the potential of blending ethanol with natural gasoline to produce Flex-Fuels (ASTM D5798-13a) and high-octane, mid-level ethanol blends. Eight natural gasoline samples were collected from pipeline companies or ethanol producers around the United States.
The objective of this work was to measure knock resistance metrics for ethanol-hydrocarbon blends with a primary focus on development of methods to measure the heat of vaporization (HOV). Blends of ethanol at 10 to 50 volume percent were prepared with three gasoline blendstocks and a natural gasoline.
High-octane fuels (HOFs) such as mid-level ethanol blends can be leveraged to design vehicles with increased engine efficiency, but producing these fuels at refineries may be subject to energy efficiency penalties. It has been questioned whether, on a well-to-wheels (WTW) basis, the use of HOFs in the vehicles designed for HOF has net greenhouse gas (GHG) emission benefits.
Vimmerstedt, L. J., Bush, B. W., Hsu, D. D., Inman, D. and Peterson, S. O. (2014), Maturation of biomass-to-biofuels conversion technology pathways for rapid expansion of biofuels production: a system dynamics perspective. Biofuels, Bioprod. Bioref.. doi: 10.1002/bbb.1515
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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
Biomass Scenario Model: Supplemental Tableau workbook for Christopher M Clark et al 2013 Environ. Res. Lett. 8 025016 doi:10.1088/1748-9326/8/2/025016 Growing a sustainable biofuels industry: economics, environmental considerations, and the role of the Conservation Reserve Program
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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.
In support of the national goals for biofuel use in the United States, numerous technologies have been developed that convert biomass to biofuels. Some of these biomass to biofuel conversion technology pathways are operating at commercial scales, while others are in earlier stages of development. The advancement of a new pathway toward commercialization involves various types of progress, including yield improvements, process engineering, and financial performance.
Indicators are needed to assess environmental sustainability of bioenergy systems. Effective indicators
will help in the quantification of benefits and costs of bioenergy options and resource uses. We identify
19 measurable indicators for soil quality, water quality and quantity, greenhouse gases, biodiversity, air
quality, and productivity, building on existing knowledge and on national and international programs
that are seeking ways to assess sustainable bioenergy. Together, this suite of indicators is hypothesized
Despite recent claims to the contrary, plant-based fuels developed in economically and environmentally sensible ways can contribute significantly to the nation’s— indeed, the world’s—energy security while providing a host of benefits for many people worldwide.
IN THEIR REPORTS IN THE 29 FEBRUARY ISSUE (“LAND CLEARING AND THE BIOFUEL CARBON debt,” J. Fargione et al., p. 1235, and “Use of U.S. croplands for biofuels increases greenhouse gases through emissions from land-use change,” T. Searchinger et al., p. 1238), the authors do not provide adequate support for their claim that biofuels cause high emissions due to land-use change. The conclusions of both papers depend on the misleading premise that biofuel production causes forests and grasslands to be converted to agriculture.
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.
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.
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.
This paper offers a graphical exposition of the GTAP model of global trade. Particular emphasis is placed on the accounting, or equilibrium, relationships in the model. It begins with a treatment of the a one region version of GTAP, thereafter adding a rest of world region to highlight the treatment of trade flows in the model. The implementation of policy instruments in GTAP is also explored, using simple supply-demand graphics. The material provided in this paper was first developed as an introduction to GTAP for participants taking the annual short course.
This report discusses the development of greenhouse gas (GHG) emissions estimates for the production of Fischer-Tropsch (FT) derived fuels (in particular, FT diesel), makes comparisons of these estimates to reported literature values for petroleum-derived diesel, and outlines strategies for substantially reducing these emissions.
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.
Biomass Scenario Model Zotero References
National Renewable Energy Laboratory
Despite a rapid worldwide expansion of the biofuel industry, there is a lack of consensus within the scientific community about the potential of biofuels to reduce reliance on petroleum and decrease greenhouse gas (GHG) emissions. Although life cycle assessment provides a means to quantify these potential benefits and environmental impacts, existing methods limit direct comparison within and between different biofuel systems because of inconsistencies in performance metrics, system boundaries, and underlying parameter values.