A review of variability in indirect land use change assessment and modeling in biofuel policy

Abstract

Abstract The inclusion of indirect land use change (ILUC) can dramatically affect the calculated greenhouse gas (GHG) benefits of biofuels in comparison to conventional fuels. Due to the potential magnitude and impacts of ILUC, this concept is being included in many biofuel policies, such as the U.S. Renewable Fuel Standard (RFS2) and California's Low Carbon Fuel Standard (LCFS). The approaches to modeling ILUC are complex and fraught with uncertainties, and results tend to lack agreement. In this work, we have investigated the modeling approaches and emission factor databases employed to determine their effects on ILUC variability in several key studies, with particular focus on U.S. policy. The amount and location of ILUC, which is predicted by agro-economic models, vary greatly from the studies investigated: Searchinger et al. (2008) predicted more than twice the amount of land conversion compared to more recent studies that have used updated models. Even more influential, yet more understated, is the estimation of the type of land converted, since conversion of forests results in significantly greater GHG emissions than conversion from other land types, and RFS2 and LCFS have estimated only a fraction of conversion of forest in comparison to Searchinger. Additionally, many studies investigated have relied on the Woods Hole Research Center (WHRC) emission factor database to determine GHG emissions from ILUC, but each has applied data differently to arrive at different results. It is recognized that this database is coarse, so a more spatially explicit approach in the Winrock database, which has carbon stock data for over 750 regions worldwide, has been used in the RFS2 fuel policy.