Scown et al. [18] considered a number of domestic U.S. scenarios for the production of 39.7 billion liters/year of ethanol from miscanthus, allowing only cropland or CRP lands to be converted to miscanthus production. These authors modelled productivity of miscanthus with Miscanmod at the county level. A model proposed byMatthews and Grogan [19] was used to estimate the SOC content of converted land. SOC changes were aggregated to the county level from a 90-meter resolution. In their calculation of LUC GHG emissions, Scown et al. [18] did not consider the impact of land management history on SOC content. Their study concluded that on net 3.4 to 16 g CO2e/MJ would be sequestered as a result of SOC changes. Separately, Davis et al. [20] considered the conversion of 30% of domestic (U.S.) land currently in corn production to miscanthus or switchgrass (fertilized or unfertilized) production. They used DAYCENT to simulate
regional miscanthus and switchgrass cultivation in the central U.S. and identified lower GHG fluxes from cultivation when either crop was grown in place of corn. The reductions after 10 years (1.9% for switchgrass with fertilization and 19% for miscanthus) came from both reduction in fertilizer-derived N2O emissions and increased carbon sequestration. Similarly, Qin et al. [21] showed that SOC content increases by 50 and 80% when land is converted from corn cultivation to switchgrass and miscanthus, respectively. EPA has estimated LUC GHG emissions for cellulosic ethanol derived from corn stover (−10 g CO2e/MJ) and switchgrass (12 g CO2e/MJ) [11]. CARB has examined forest residue and farmed trees as feedstocks for cellulosic ethanol [22,23]. The agency developed preliminary LUC GHG estimates for the latter feedstock, which is not examined in our current study. The above literature summary highlights two limitationsof previous studies of LUC GHG emissions associatedwith cellulosic ethanol production. First, application of worldwide CGE modelling to LUC GHG calculations
for cellulosic ethanol has been limited to EPA and CARB analyses for switchgrass and corn stover. Second, SOC emission factors have either been developed for very
specific lands (e.g., CRP or agricultural lands) or at the national or regional scale for other land types, as in the CARB and EPA analyses. In our study, we sought to address these two limitations of the current literature. First, we used worldwide LUC results for four biofuel production scenarios (Table 1) as modelled with Purdue University’s Global Trade Analysis Project (GTAP) CGE model [24]. The modelling considered domestic U.S. production of ethanol from four feedstocks: corn, corn ethanol, switchgrass, and miscanthus. Second, we applied finer-level SOC emission factors (EF) than have
been used in previous analyses for all land categories, including forests. We developed a modelling framework Dunn et al. Biotechnology for Biofuels 2013, 6:51 Page 2 of 13
Scown et al. [18] considered a number of domestic U.S. scenarios for the production of 39.7 billion liters/year of ethanol from miscanthus, allowing only cropland or CRP lands to be converted to miscanthus production. These authors modelled productivity of miscanthus with Miscanmod at the county level. A model proposed byMatthews and Grogan [19] was used to estimate the SOC content of converted land. SOC changes were aggregated to the county level from a 90-meter resolution. In their calculation of LUC GHG emissions, Scown et al. [18] did not consider the impact of land management history on SOC content. Their study concluded that on net 3.4 to 16 g CO2e/MJ would be sequestered as a result of SOC changes. Separately, Davis et al. [20] considered the conversion of 30% of domestic (U.S.) land currently in corn production to miscanthus or switchgrass (fertilized or unfertilized) production. They used DAYCENT to simulate
regional miscanthus and switchgrass cultivation in the central U.S. and identified lower GHG fluxes from cultivation when either crop was grown in place of corn. The reductions after 10 years (1.9% for switchgrass with fertilization and 19% for miscanthus) came from both reduction in fertilizer-derived N2O emissions and increased carbon sequestration. Similarly, Qin et al. [21] showed that SOC content increases by 50 and 80% when land is converted from corn cultivation to switchgrass and miscanthus, respectively. EPA has estimated LUC GHG emissions for cellulosic ethanol derived from corn stover (−10 g CO2e/MJ) and switchgrass (12 g CO2e/MJ) [11]. CARB has examined forest residue and farmed trees as feedstocks for cellulosic ethanol [22,23]. The agency developed preliminary LUC GHG estimates for the latter feedstock, which is not examined in our current study. The above literature summary highlights two limitationsof previous studies of LUC GHG emissions associatedwith cellulosic ethanol production. First, application of worldwide CGE modelling to LUC GHG calculations
for cellulosic ethanol has been limited to EPA and CARB analyses for switchgrass and corn stover. Second, SOC emission factors have either been developed for very
specific lands (e.g., CRP or agricultural lands) or at the national or regional scale for other land types, as in the CARB and EPA analyses. In our study, we sought to address these two limitations of the current literature. First, we used worldwide LUC results for four biofuel production scenarios (Table 1) as modelled with Purdue University’s Global Trade Analysis Project (GTAP) CGE model [24]. The modelling considered domestic U.S. production of ethanol from four feedstocks: corn, corn ethanol, switchgrass, and miscanthus. Second, we applied finer-level SOC emission factors (EF) than have
been used in previous analyses for all land categories, including forests. We developed a modelling framework Dunn et al. Biotechnology for Biofuels 2013, 6:51 Page 2 of 13
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