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.
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.
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 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.
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.
This paper estimates household preferences for ethanol as a gasoline substitute. I develop a theoretical
model linking the shape of the ethanol demand curve to the distribution of price ratios at which individual
households switch fuels. I estimate the model using data from many retail fueling stations. Demand
is price-sensitive with a mean elasticity of 2.5�3.5. I find that preferences are heterogeneous with many
households willing to pay a premium for ethanol. This reduces the simulated cost of an ethanol content
A primary objective of current U.S. biofuel law – the “Energy Independence and Security Act of 2007” (EISA) – is to reduce dependence on imported oil, but the law also requires biofuels to meet carbon emission reduction thresholds relative to petroleum fuels. EISA created a renewable fuel standard with annual targets for U.S. biofuel use that climb gradually from 9 billion gallons per year in 2008 to 36 billion gallons (or about 136 billion liters) of biofuels per year by 2022. The most controversial aspects of U.S.
This report is an update of the original version, which was published in October 2008. This updated report includes results from the complete 16-vehicle fleet (the original report included only the first 13 vehicles tested) as well as corrections to minor errors identified in some of the originally reported data. Conclusions drawn from the complete dataset are nearly identical to those from the
original 13-vehicle fleet but with increased statistical confidence.
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.
The objective of the research here is to more carefully investigate the claims of localized
impacts on two fronts. The first is the impact a local ethanol plant has on the rate of agricultural
land conversion to other uses (if an ethanol plant increases the value of local agricultural land as
a result of increased commodity prices, one might expect a slower rate of conversion relative to
other communities). Second, we investigate whether the siting of an ethanol plant has had a
negative impact on local residential land values.
This study is a statistical analysis to estimate the significance of factors that influence the volume of E85 sales to the general public in Minnesota from 1997 to 2006.
The Biomass Program is one of the nine technology development programs within the Office of Energy Efficiency and Renewable Energy (EERE) at the U.S. Department of Energy (DOE). This 2011 Multi-Year Program Plan (MYPP) sets forth the goals and structure of the Biomass Program. It identifies the research, development, demonstration, and deployment (RDD&D) activities the Program will focus on over the next five years, and outlines why these activities are important to meeting the energy and sustainability challenges facing the nation.
This report identify the issues associated with intermediate ethanol blends with an emphasis on the end-use or
vehicle impacts of increased ethanol levels and compile a current and complete bibliography of key references on intermediate ethanol blends.
The market for E85�a fuel blend of 85 percent ethanol and 15 percent gasoline�is small
but growing rapidly. I use data for E85 sales at fueling stations in Minnesota to estimate
demand for E85 as a function of retail E85 and gasoline prices. I find that demand is
highly sensitive to price changes, with an own-price elasticity as high as -13 and a gasolineprice
elasticity as high as 16 at sample mean price levels. Demand is most sensitive to
price changes when the relative price of E85 is at an intermediate level, at which point
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.