Argonne lowers land use change GHG emissions for corn ethanol

Source: By Susanne Retka Schill, Ethanol Producer Magazine • Posted: Monday, October 13, 2014

The estimation of greenhouse gas (GHG) emissions due to land use change (LUC) for corn ethanol has been ratcheted down by Argonne National Laboratory. The recently published manual for the Carbon Calculator for Land Use Change from Biofuels Production puts that value at 7.6 gCO2e/MJ, down from 9.0 in last year’s modeling and four-times lower than the 28 gCO2e/MJ value used by the U.S. EPA in determining GHG reduction relative to gasoline for the renewable fuels standard.

In the most recent modelling, the Argonne CCLUB also estimated LUC for corn stover at a negative 0.7 gCO2e/MJ, switchgrass at negative 3.5 and miscanthus negative 20.1. Thus, miscanthus LUC results in net carbon sequestration. The paper notes that the yields for miscanthus and switchgrass vary greatly depending upon location and management practices, which has a big impact on emissions estimates.

“CCLUB was developed to help GREET users and the biofuels community understand how land use change emissions are calculated,” explained Jennifer Dunn, biofuels life cycle analysis lead at ANL. “We tried to use the best available data.” Argonne’s greenhouse gases, regulated emission and energy use in transportation (GREET) model is widely used for life cycle analyses. CCLUB can be used as module within GREET when analyzing the four feedstocks covered in CCLUB—corn, corn stover, switchgrass and miscanthus.

The newly released 35-page CCLUB manual documents the databases and boundaries used in the modeling and describes the refinements made each year as the model has been used.  It utilizes data from Purdue University’s Global Trade Analysis Project model for area land change data. Winrock data is combined with GTAP for the modeling of international land use change. Above ground nonsoil carbon content for forest ecosystems come from a USDA Forest Service model and shrubland transitions are also incorporated.

The reason the corn numbers in this modeling are significantly lower than other estimates is the use of soil organic matter modeling, explained Steffen Mueller, principle economist at the University of Chicago Energy Resource Center and a co-author on the CCLUB paper. “The key changes come from the biophysical carbon model we use, where we can make a soil carbon adjustment for each feedstock.”  Feedstock and belowground carbon content values used in CCLUB are based on CENTURY’s soil organic matter model.  The 2012 data from CCLUB used state-level data for the soil organic matter modeling and the 2013 data used county level data. This year’s model was able to incorporate even higher resolutions for soil organic matter and include data for carbon impacts found in deeper soils.

In future modeling work, the Argonne team intends to address several issues: “For example, current SOC modeling of conversion to cropland assumes that cropland is essentially planted in corn, but GTAP results may indicate other crops could be planted as well as part of crop switching,” the manual said. “… We may seek to model transitions to specific crop types beyond corn. Secondly, corn agriculture is currently modeled as continuous corn, but actual practice may be to integrate soy rotations. We will consider different rotation scenarios for inclusion in CCLUB. Finally, we currently model the land use history of cropland-pastureland as 50 years as cropland followed by 25 years of pasture and 25 years of cropland. Actual land use history may include more frequent changes between these two land uses. We may develop SOC emission factors for land transitions involving cropland-pastureland that reflect a more defined land use history.”