biorefinery

This dataset was utilized in a report to highlight parameters that affect near-term sustainable supply of corn stover and forest resources at $56 and $74 per dry ton delivered. While the report focus is restricted to 2018, the modeling runs are available from 2016-2022. In the 2016 Billion-ton Report (BT16), two stover cases were presented. In this dataset, we vary technical levels of those assumptions to measure stover supply response and to evaluate the major determinants of stover supply. In each of these cases, the supply is modeled first at the farmgate at prices up to $80 per dry ton for five deterministic scenarios. Building on this dataset, a supplementary dataset of delivered supply was modeled for 800k dry ton per year capacity facilities in two facility siting approaches. Results were summarized across delivered supply curves for twelve scenarios. The resulting supply curves are highly elastic, resulting in a range of potential supplies across scenarios at specified prices. Interactive visualization of these data allows exploration into any specified nth plant supply sensitivity to key variables and spatial distribution of stover resources.

The analysis is economic supply risk and doesn’t account for disruptions from competing demands, namely livestock feed and bedding markets.

Production costs of bio-ethanol from sugarcane in Brazil have declined continuously over the last three decades. The aims of this study are to determine underlying reasons behind these cost reductions, and to assess whether the experience curve concept can be used to describe the development of feedstock costs and industrial production costs. The analysis was performed using average national costs data, a number of prices (as a proxy for production costs) and data on annual Brazilian production volumes. Results show that the progress ratio (PR) for feedstock costs is 0.68 and 0.81 for industrial costs (excluding feedstock costs). The experience curve of total production costs results in a PR of 0.80. Cost breakdowns of sugarcane production show that all sub-processes contributed to the total, but that increasing yields have been the main driving force. Industrial costs mainly decreased because of increasing scales of the ethanol plants. Total production costs at present are approximately 340 US$/methanol3 (16 US$/GJ). Based on the experience curves for feedstock and industrial costs, total ethanol production costs in 2020 are estimated between US$ 200 and 260/m3 (9.4–12.2 US$/GJ). We conclude that using disaggregated experience curves for feedstock and industrial processing costs provide more insights into the factors that lowered costs in the past, and allow more accurate estimations for future cost developments.

The Renewable Fuels Association (RFA) provides an interactive map of ethanol biorefinery locations in the U.S.

The water consumption and agrochemical use during biofuel production could adversely impact both availability and quality of a precious resource.

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. Our estimates of 1−2 cents per L of ethanol blend for downstream rail or truck transportation remain a relatively small fraction of total fuel cost. However, for even the relatively small blends of ethanol modeled, the transportation infrastructure demands would be comparably larger than the current demands of petroleum. Thus if ethanol is to be competitive in the long run, then in addition to process efficiency improvements, more efficient transportation infrastructure will need to be developed, such as pipelines. In addition to these results, national and regional policy challenges on how to pay for and optimize a new fuel and distribution infrastructure in the United States are discussed.

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
exemptions, and methyl tertiary-butyl ether bans provided some counties with a comparative advantage in attracting ethanol plants.

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 2011 MYPP is intended for use as an operational guide to help the Biomass Program manage and coordinate its activities, and as a resource to help articulate its mission and goals to management and the public.