analysis

The use of corn for ethanol production in the United States quintupled between 2001 and 2009, generating concerns that this could lead to the conversion of forests and grasslands around the blobe, known as indirect land-use change (iLUC). Estimates of iLUC and related "food versus fuel" concerns rest on the assumption that the corn used for ethanol production in the United States would come primarily from displacing corn exports and land previously used for other crops. A number of modeling efforts based on these assumptions have projected significant iLUC from the increases in the use of corn for ethanol production. The current study tests the veracity of these assumptions through a systematic decomposition analysis of the empirical data from 2001 to 2009. The logarithmic mean divisia index decomposition method (Type I) was used to estimate contributions of different factors to meeting the corn demand for ethanol production. Results show that about 79% of the change in corn used for ethanol production can be attributed to changes in the distribution of domestic corn consumption among different uses. Increases in the domestic consumption share of corn supply contributed only about 5%. The remaining contributions were 19% from added corn production, and -2% from stock changes. Yield change accounted for about two thirds of the contributions from production changes. Thus, the results of this study provide little support for large land-use changes or diversion of corn exports because of ethanol production in the United States furing the past decade.

Adding bioenergy to the U.S. energy portfolio requires long‐term profitability for bioenergy producers and
long‐term protection of affected ecosystems. In this study, we present steps along the path toward evaluating both sides of
the sustainability equation (production and environmental) for switchgrass (Panicum virgatum) using the Soil and Water
Assessment Tool (SWAT). We modeled production of switchgrass and river flow using SWAT for current landscapes at a
regional scale. To quantify feedstock production, we compared lowland switchgrass yields simulated by SWAT with estimates
from a model based on empirical data for the eastern U.S. The two produced similar geographic patterns. Average yields
reported in field trials tended to be higher than average SWAT‐predicted yields, which may nevertheless be more
representative of production‐scale yields. As a preliminary step toward quantifying bioenergy‐related changes in water
quality, we evaluated flow predictions by the SWAT model for the Arkansas‐White‐Red river basin. We compared monthly
SWAT flow predictions to USGS measurements from 86 subbasins across the region. Although agreement was good, we
conducted an analysis of residuals (functional validation) seeking patterns to guide future model improvements. The analysis
indicated that differences between SWAT flow predictions and field data increased in downstream subbasins and in subbasins
with higher percentage of water. Together, these analyses have moved us closer to our ultimate goal of identifying areas with
high economic and environmental potential for sustainable feedstock production.

Understanding the Growth of the Cellulosic Ethanol Industry, D. Sandor and R. Wallace, National Renewable Energy Laboratory, S. Peterson The Peterson Group, Technical Report, NREL/TP-150-42120 April 2008