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.
In the corn ethanol industry, the ability of plants to obtain favorable prices through marketing decisions is considered important for their overall economic performance. Based on a panel of surveyed of ethanol plants we extend data envelopment analysis (DEA) to decompose the economic efficiency of plants into conventional sources (technical and allocative efficiency) and a new component we call marketing efficiency.
The rapidly expanding biofuel industry has changed the fundamentals of U.S. agricultural commodity markets. Increasing ethanol and biodiesel production has generated a fast-growing demand for corn and soybean products, which competes with the well-established domestic livestock industry and foreign buyers. Meanwhile, the co-products of biofuel production are replacing or displacing coarse grains and oilseed meal in feed rations for livestock.
The location of ethanol plants is determined by infrastructure, product and input markets, fiscal attributes of local communities, and state and federal incentives. This empirical
analysis uses probit regression along with spatial clustering methods to analyze investment activity of ethanol plants at the county level for the lower U.S. 48 states from 2000 to 2007.
The availability of feedstock dominates the site selection decision. Other factors, such as access to navigable rivers or railroads, product markets, producer credit and excise tax
A method is presented, which estimates the potential for power production from agriculture residues. A GIS decision support system (DSS) has been developed, which implements the method and provides the tools to identify the geographic distribution of the economically exploited biomass potential. The procedure introduces a four level analysis to determine the
theoretical, available, technological and economically exploitable potential. The DSS handles all possible restrictions and