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This report evaluates infrastructure implications for a high-octane fuel, i.e., a blend of 25% denatured ethanol and 75% gasoline (E25) or higher (E25+), for use with a new high-efficiency type of vehicle. E25+ is under consideration due to federal regulations requiring the use of more renewable fuels and improvements in fuel economy. The existing transportation fuel infrastructure may not be completely compatible with a mid-level ethanol blend (blends above E15 up to E50).

Author(s):
K. Moriarty , M. Kass , T. Theiss

The compatibility of plastic materials used in fuel storage and dispensing applications was determined for an off-highway diesel fuel
and a blend containing 20% bio-oil (Bio20) derived from a fast pyrolysis process. Bio20 is not to be confused with B20, which is a
diesel blend containing 20% biodiesel. The feedstock, processing, and chemistry of biodiesel are markedly different from bio-oil.
Plastic materials included those identified for use as seals, coatings, piping and fiberglass resins, but many are also used in vehicle

Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

The compatibility of plastic materials used in fuel storage and dispensing applications was determined for a test fuel representing
gasoline blended with 10% ethanol. Prior investigations were performed on gasoline fuels containing 25, 50 and 85% ethanol, but the
knowledge gap existing from 0 to 25% ethanol precluded accurate compatibility assessment of low level blends, especially for the
current E10 fuel (gasoline containing 10% ethanol) used in most filling stations, and the recently accepted E15 fuel blend (gasoline
blended with up to15% ethanol).

Author(s):
Michael Kass
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

The compatibility of elastomer materials used in fuel storage and dispensing applications was determined for an off-highway diesel
fuel and a blend containing 20% bio-oil (Bio20) derived from a fast pyrolysis process. (This fuel blend is not to be confused with B20,
which is a blend of diesel fuel with 20% biodiesel.) The elastomer types evaluated in this study included fluorocarbon, fluorosilicone,
acrylonitrile rubber (NBR), styrene butadiene rubber (SBR), polyurethane, neoprene, and silicone. All of these elastomer types are

Author(s):
Michael Kass
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

Excess nutrients from agriculture in the Mississippi River drainage, USA have degraded water quality in
freshwaters and contributed to anoxic conditions in downstream estuaries. Consequently, water quality is a
significant concern associated with conversion of lands to bioenergy production. This study focused on the
Arkansas-White-Red river basin (AWR), one of five major river basins draining to the Mississippi River. The
AWR has a strong precipitation gradient from east to west, and advanced cellulosic feedstocks are projected to

Author(s):
Henriette I. Jager , Latha M. Baskaran   , Peter E. Schweizer   , Anthony F. Turhollow   , Craig C. Brandt  , Raghavan Srinivasan
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

Understanding how large-scale bioenergy production can affect biodiversity and ecosystems is important if society is to meet current and future sustainable development goals. A variety of bioenergy production systems have been established within different contexts throughout the Pan American region, with wide-ranging results in terms of documented and projected effects on biodiversity and ecosystems.

A framework for selecting and evaluating indicators of bioenergy sustainability is presented.
This framework is designed to facilitate decision-making about which indicators are useful for assessing
sustainability of bioenergy systems and supporting their deployment. Efforts to develop sustainability
indicators in the United States and Europe are reviewed. The fi rst steps of the framework for
indicator selection are defi ning the sustainability goals and other goals for a bioenergy project or program,

Author(s):
Virginia Dale
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

For analyzing sustainability of algal biofuels, we identify 16 environmental indicators that fall into six categories: soil quality, water quality and quantity, air quality, greenhouse gas emissions, biodiversity, and productivity. Indicators are selected to be practical, widely applicable, predictable in response, anticipatory of future changes, independent of scale, and responsive to management.

Author(s):
R. A. Efroymson
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

Agroecosystem models that can incorporate management practices and quantify environmental effects
are necessary to assess sustainability-associated food and bioenergy production across spatial scales.
However, most agroecosystem models are designed for a plot scale. Tremendous computational capacity
on simulations and datasets is needed when large scales of high-resolution spatial simulations are conducted.
We used the message passing interface (MPI) parallel technique and developed a master–slave

Author(s):
S. Kang

In order to aid operations that promote sustainability goals, researchers and stakeholders use sustainability assessments.  Although assessments take various forms, many utilize diverse sets of indicators numbering anywhere from two to over 2000. Indices, composite indicators, or aggregate values are used to simplify high dimensional and complex data sets and to clarify assessment results. Although the choice of aggregation function is a key component in the development of the assessment, there are fewliterature examples to guide appropriate

Author(s):
Nathan Pollesch
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

As with all land transformation activities, effects on biodiversity and ecosystem services of producing feedstocks for biofuels are highly variable and context specific.  Advances toward more sustainable biofuel production benefit from a system's perspective, recognizing spatial heterogeneity and scale, landscape-design principles, and addressing the influences of context such as the particular products and their distribution, policy background, stakeholder values, location, temporal influences, and baseline conditions.  Deploying biofuels in a manner to reduce effects on biodiversity

Author(s):
C.A. Joly
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

Abstract: Farmgate prices (i.e. price delivered roadside ready for loading and transport) for biomass feedstocks directly infl uence biofuel prices. Using the latest available data, marginal (i.e. price for the last ton) farmgate prices of $51, $63, and $67 dry ton–1 ($2011) are projected as necessary to provide 21 billion gallons of biofuels from about 250 million dry tons of terrestrial feedstocks in 2022 under price-run deterministic, demand-run deterministic, and stochastic simulations, respectively.

Author(s):
Matthew Langholtz , Laurence Eaton , Anthony Turhollow , Michael Hilliard

As U.S. energy policy turns to bioenergy, and second-generation biofuels in particular, to foster energy security and environmental benefits, consideration should be given to the implications of climate risk for the incipient bioenergy industry. As a case-in-point, we review evidence from the 2012 U.S. drought, underscoring the risk of extreme weather events to the agricultural sector in general, and the bioenergy supply chain in particular, including reductions in feedstock production and higher prices for agricultural commodities and biofuels.

Author(s):
Matthew Langholtz

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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Author(s):
NREL

Understanding the development of the biofuels industry in the United States is important to policymakers and industry. The Biomass Scenario Model (BSM) is a system dynamics model of the biomass-to-biofuels system that can be used to explore policy effects on biofuels development. Because of the complexity of the model, as well as the wide range of possible future conditions that affect biofuels industry development, we have not developed a single reference case but instead developed a set of specific scenarios that provide various contexts for our analyses.

Author(s):
Inman, D.; Vimmerstedt, L.; Bush, B.; Peterson, S.
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

a b s t r a c t
As U.S. energy policy turns to bioenergy, and second-generation biofuels in particular, to
foster energy security and environmental benefits, consideration should be given to the
implications of climate risk for the incipient bioenergy industry. As a case-in-point, we
review evidence from the 2012 U.S. drought, underscoring the risk of extreme weather
events to the agricultural sector in general, and the bioenergy supply chain in particular,
including reductions in feedstock production and higher prices for agricultural

Author(s):
ORNL

Understanding the environmental effects of alternative fuel production is critical to characterizing the sustainability of energy resources to inform policy and regulatory decisions. The magnitudes of these environmental effects vary according to the intensity and scale of fuel production along each step of the supply chain. We compare the spatial extent and temporal duration of ethanol and gasoline production processes and environmental effects based on a literature review and then synthesize the scale differences on space-time diagrams.

Organization:
DOE
Author(s):
Parish ES , Kline KL , Dale VH , Efroymson RA , McBride AC , Johnson TL , Hilliard MR , Bielicki JM
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.