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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.

http://jgcri.github.io/gcam-doc/

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

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.

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

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.

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

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.

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

The database summarizes a very broad set of old and new standing biomass data from plantation-grown hardwoods and softwoods established under a wide range of conditions across the United States and Canada. The WCYP database, together with this document, is being published to disseminate information on what is available in the literature with respect to yield evaluations and to inform people that not all yield data in the open literature are suitable for evaluation of “potential” regional yields.

Author(s):
Lynn Wright

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.

Author(s):
Peterson, Steve

A woody crop yield potential (WCYP) database was created containing yield results with as much associated information as was available concerning the sites, soils, and experimental treatments. The database summarizes a very broad set of old and new standing biomass data from plantation-grown hardwoods and softwoods established under a wide range of conditions across the United States and Canada.

Author(s):
Lynn Wright

Nationwide spatial dataset representing the polygon areas for first-generation suitability analysis of potentially suitable areas for microalgae open ponds. The PNNL microalgae growth model results for each site are included in the attribute table and assume growth based on theoretical limits. Sites represent a minimum mapping unit of 490 hectares. Land suitability included area less than or equal to 1% slope on non-agricultural, undeveloped or low‐density developed, nonsensitive, generally noncompetitive land was considered for microalgal culture facilities.

Biofuels are promoted in the United States through aggressive legislation, as one part of an overall strategy to lessen dependence on imported energy as well as to reduce the emissions of greenhouse gases (Office of the Biomass Program and Energy Efficiency and Renewable Energy, 2008). For example, the Energy Independence and Security Act of 2007 (EISA) mandates 36 billion gallons of renewable liquid transportation fuel in the U.S. marketplace by the year 2022 (U.S. Government, 2007).

Author(s):
Emily Newes, Daniel Inman, Brian Bush

Microalgae are receiving increased global attention as a potential sustainable “energy crop”for biofuel production. An important step to realizing the potential of algae is quantifying the demands commercial‐scale algal biofuel production will place on water and land resources. We present a high‐resolution spatiotemporal assessment that brings to bear fundamental questions of where production can occur, how many land and water resources are required, and how much energy is produced.

Author(s):
Wigmosta, Mark

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.

Author(s):
Keith L. Kline , Gbadebo Oladosu

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.

Author(s):
Fabiosa,Jacinto F.

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.

Author(s):
William R. Morrow

Human actions are altering the terrestrial environment at unprecedented rates, magnitudes, and spatial scales. Landcover change stemming from human land uses represents a major source and a major element of global environmental change. Not only are the global-level data on landuse and land-cover change relatively poor, but we need a much better understanding of the underlying driving forces for these changes. Many forces have been proposed as significant, but single-factor explanations of land transformation have proved to be inadequate.

Author(s):
Turner,B.L.

We present a system dynamics global LUC model intended to examine LUC attributed to biofuel production. The model has major global land system stocks and flows and can be exercised under different food and biofuel demand assumptions. This model provides insights into the drivers and dynamic interactions of LUC, population, dietary choices, and biofuel policy rather than a precise number generator.

The Census of Agriculture, taken every five years, is a complete count of U.S. farms and ranches and the people who operate them. The Census looks at land use and ownership, operator characteristics, production practices, income and expenditures. For America’s farmers and ranchers, the Census of Agriculture is their voice, their future and their responsibility.

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

The estimation of greenhouse gas (GHG) emissions from a change in land-use and management resulting from growing biofuel feedstocks has undergone extensive – and often contentious – scientific and policy debate. Emergent renewable fuel policies require life cycle GHG emission accounting that includes biofuel-induced global land-use change (LUC) GHG emissions. However, the science of LUC generally, and biofuels-induced LUC specifically, is nascent and underpinned with great uncertainty.