The biobased economy is playing an increasingly important role in the American economy.
Through innovations in renewable energies and the emergence of a new generation of biobased products, the sectors that drive the biobased economy are providing job creation and economic growth. To further understand and analyze trends in the biobased economy, this report compares 2011 and 2016 report data.
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.
Social and economic indicators can be used to support design of sustainable energy systems. Indicators representing categories of social well-being, energy security, external trade, profitability, resource conservation, and social acceptability have not yet been measured in published sustainability assessments for commercial algal biofuel facilities.
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,
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
Eucalyptus is a fast-growing tree native to Australia and could be used to supply biomass for bioenergy and other purposes along the coastal regions of the southeastern United States (USA). At a farmgate price of $66 dry Mg−1, a potential supply of 27 to 41.3 million dry Mg year−1 of Eucalyptus could be produced on about 1.75 million ha in the southeastern USA. A proposed suite of indicators provides a practical and consistent way to measure the sustainability of a particular situation where Eucalyptus might be grown as a feedstock for conversion to bioenergy.
Agricultural sustainability considers the effects of farm activities on social, economic, and environmental conditions at local and regional scales. Adoption of more sustainable agricultural practices entails defining sustainability, developing easily measured indicators of sustainability, moving toward integrated agricultural systems, and offering incentives or imposing regulations to affect farmer behavior.
Landscape implications of bioenergy feedstock choices are significant and depend on land-use practices and their environmental impacts. Although land-use changes and carbon emissions associated with bioenergy feedstock production are dynamic and complicated, lignocellulosic feedstocks may offer opportunities that enhance sustainability when compared to other transportation fuel alternatives.
Developing scientific criteria and indicators should play a critical role in charting a sustainable path for the rapidly developing biofuel industry. The challenge ahead in developing such criteria and indicators is to address the limitations on data and modeling.
Developing scientific criteria and indicators should play a critical role in charting a sustainable path for the rapidly developing biofuel industry. The challenge ahead in developing such criteria and indicators is to address the limitations on data and modeling.
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.
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.
This paper connects the science of sustainability theory with applied aspects of sustainability deployment.
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.
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.
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