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Logging and mill residues are currently the largest sources of woody biomass for bioenergy in the US, but short-rotation woody crops (SRWCs) are expected to become a larger contributor to biomass production, primarily on lands marginal for food production. However, there are very few studies on the environmental effects of SRWCs, and most have been conducted at stand rather than at watershed scales.

Organization:
DOE
Author(s):
Natalie A. Griffiths , Benjamin M. Rau , Kellie B. Vache , Gregory Starr , Menberu M. Bitew , Doug P. Aubrey , James A. Martin , Elizabeth Benton , C. Rhett Jackson
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

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.

Author(s):
Maggie Davis , Laurence Eaton , Matt Langholtz
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

The U.S. Department of Energy’s (DOE’s) Co-Optimization (Co-Optima) initiative is accelerating the introduction of affordable, scalable, and sustainable fuels and high-efficiency, low-emission engines with a first-of-its-kind effort to simultaneously tackle fuel and engine research and development (R&D).

Author(s):
John Farrell , John Holladay , Robert Wagner
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.

Corn’s (Zea mays L.) stover is a potential nonfood, herbaceous bioenergy feedstock. A vital aspect of utilizing stover for bioenergy production is to establish sustainable harvest criteria that avoid exacerbating soil erosion or degrading soil organic carbon (SOC) levels. Our goal is to empirically estimate the minimum residue return rate required to sustain SOC levels at numerous locations and to identify which macroscale factors affect empirical estimates.

Author(s):
Jane M. F. Johnson , Jeffrey M. Novak , Gary E. Varvel , Diane E. Stott , Shannon L. Osborne , Douglas L. Karlen , John A. Lamb , John Baker , Paul R. Adler

To prepare for a 2014 launch of commercial scale cellulosic ethanol production from corn/maize (Zea mays L.) stover, POET-DSM near Emmetsburg, IA has been working with farmers, researchers, and equipment dealers through “Project Liberty” on harvest, transportation, and storage logistics of corn stover for the past several years. Our objective was to evaluate seven stover harvest strategies within a 50-ha (125 acres) site on very deep, moderately well to poorly drained Mollisols, developed in calcareous glacial till.

Author(s):
Stuart J. Birrell , Douglas L. Karlen , Adam Wirt

Agricultural residues have been identified as a significant potential resource for bioenergy production, but serious questions remain about the sustainability of harvesting residues. Agricultural residues play an important role in limiting soil erosion from wind and water and in maintaining soil organic carbon. Because of this, multiple factors must be considered when assessing sustainable residue harvest limits.

Author(s):
D. Muth, Jr. , K.M. Bryden

Corn (Zea mays L.) stover is a potential bioenergy feedstock, but little is known about the impacts of reducing stover return on yield and soil quality in the Northern US Corn Belt. Our study objectives were to measure the impact of three stover return rates (Full (~7.8 Mg ha−1 yr−1), Moderate (~3.8 Mg ha−1 yr−1) or Low (~1.5 Mg ha yr−1) Return) on corn and soybean (Glycine max. L [Merr.]) yields and on soil dynamic properties on a chisel-tilled (Chisel) field, and well- (NT1995) or newly- (NT2005) established no-till managed fields.

Author(s):
Jane M. F. Johnson , Veronica Acosta-Martinez , Cynthia A. Cambardella , Nancy W. Barbour

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

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

Net benefits of bioenergy crops, including maize and perennial grasses such as switchgrass, are a function of several factors including the soil organic carbon (SOC) sequestered by these crops. Life cycle assessments (LCA) for bioenergy crops have been conducted using models in which SOC information is usually from the top 30 to 40 cm. Information on the effects of crop management practices on SOC has been limited so LCA models have largely not included any management practice effects.

Author(s):
Ronald F. Follett , Kenneth P. Vogel , Gary E. Varvel , Robert B. Mitchell , John Kimble

Understanding the environmental effects of alternative fuel production is critical to characterizing the sustainability of energy resources to inform policy and regulatory decisions. The magnitudes of these environmental effects vary according to the intensity and scale of fuel production along each step of the supply chain. We compare the spatial extent and temporal duration of ethanol and gasoline production processes and environmental effects based on a literature review and then synthesize the scale differences on space-time diagrams.

Author(s):
Parish, Esther

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.

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

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

In January 1976, the Transportation Energy Conservation (TEC) Division of the Energy Research and Development Administration contracted with Oak Ridge National Laboratory (ORNL) to prepare a Transportation Energy Conservation Data Book to be used by TEC staff in their evaluation of current and proposed conservation strategies. The major purposes of the Data Book were to draw together, under one cover, transportation data from diverse sources, to resolve data conflicts and inconsistencies, and to produce a comprehensive document.

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.

Author(s):
J.D. van den Wall Bake