None of the fuel carbon intensities discussed above include emissions resulting from direct or indirect land use change. Direct land use emissions result from the conversion of land for the purpose of biofuel production. Indirect land use emissions arise because of land changes that occur due to the use of an existing agricultural commodity for fuel,
0 100 200 300 400 500 600 W ell -to -W he el GH G Em is sio ns (g C O2 e/m ile )
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which raises the overall price of the commodity, thereby encouraging marginal producers to cultivate previously dormant land. If land use effects are included the carbon
intensities from biomass derived fuels will increase and in some cases may be greater than fuels derived from petroleum-based fuels.
GHG emissions from land use change contribute to global climate change by affecting the ability of the soil to store or release carbon as well as the ability of the surface of the land to reflect sunlight (albedo) (IPCC, 2007). While changes in surface can affect sunlight reflection, and thus climate, the release of carbon in the soil and in above ground biomass as a result of farming practices has been an area of considerable interest for both academics and policy makers over the last several years.
Studies indicate that emissions from land use changes contribute to the overall GHG emissions associated with biofuels by increasing the net amount of carbon released into the atmosphere as a result of cultivating land for biofuels. Likewise land use changes can affect the overall carbon intensities of fossil fuels if significant land conversion occurs as a result of resource extraction. Land use emissions that result from the direct conversion of land for biofuel production have received attention in the last 5 years and are more readily quantified when compared to indirect effects (de Gorter and Just, 2009; Westhoff et al., 2008). Recently, the effect of indirect land changes has also been investigated and has been shown by initial studies to be a significant contributor to the overall life cycle of ethanol (Fargione et al., 2008; Searchinger et al., 2008). Indirect land use emissions arise because of land changes that occur due to the use of an existing agricultural commodity for fuel, which raises the overall price of the commodity, thereby encouraging marginal producers to cultivate previously dormant land. Because such effects are a result of changes in the worldwide economy, global economic and agricultural models are
required to calculate such impacts. While developing a global economic model is beyond the scope of this project models developed by others can be used to compare what the possible emissions associated with indirect land use are. As shown in Table 6, emissions values were gathered to compared the land use emissions from of several recent studies examining worldwide corn ethanol production. As indicated the first study published by Seachinger et al. (2008) calculated that emissions were 104 gCO2e/MJ, which is more
than all other emissions of the corn ethanol lifecycle combined. More recent studies have lowered the estimated emissions to 20-30 gCO2e/MJ, and highlight the importance of
factors such as assumed corn yield rates on newly converted lands, fertilization rates, future yield growth, and coproduct credits for DGS, among others. The authors of all of these analyses emphasize the uncertain nature of land use emissions and that
disagreements exist to whether land use changes are quantifiable. Most researchers agree that while land use change emissions are highly uncertain, there omission in a lifecycle analysis of fuels can lead to results that do not accurately depict the true nature of greenhouse gas emissions from transportation fuels.
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Table 6: Land use emissions for corn ethanol from different studies.
1Searchinger et al. reported their results in terms of a 55.92 billion liter increase in ethanol production which resulted in a 10.8 million hectare change in global land use (Searchinger et al., 2008). 2The emissions based on analysis to meet the California low carbon fuel standard (CARB, 2010). 3Simulated global land use changes due to the US ethanol production: with yield and population growth after 2006 (Tyner et al., 2010).
4(EPA, 2010)
In the present study we did not have sufficient data to identify the contributions of individual fuels to model worldwide direct and indirect land use emissions. Rather, we sought to model what land use emissions would occur within MN as a result of a policy change. As discussed in the synthesis report, the policy model was used to calculate the quantity and mix of transportation fuel that resulted from a specific policy. These fuel demands were then input into the agricultural and economic model to examine the amount of land required in MN to supply the biomass needed for biofuel production as a result of a specific policy. Land use changes from the economic model were then used to model the quantity of emissions that resulted from shifting land use from dormant to crop production as a result of different policies.
For our analysis we examined two scenarios, a reference scenario in which there is no legislation regulating the carbon content of fuels and one in which a low carbon fuel standard is enacted. The resulting change in fuel demand for each policy scenario was calculated using the policy linkages model as shown in Figure 14 (to be verified in the other reports once they are finalized) of the policy modeling report associated with this study. The fuel demands were input into the agricultural and economic model, which calculated the land required to produce biomass for each scenario’s fuel mix (see
synthesis report and other appendices for further detail). In order to model the change in land use required to supply all of MN’s fuels, we used results from the agricultural and economic model shown in Table B of the agriculture economic model from this study which sought to keep grain exports constant, so that MN would not produce more
biofuels by shifting grain production to other states. With these constraints the economic model would not produce results that met the biodiesel production while maintaining
Ethanol
(gCO2e/MJ) Notes
30 Emissions based on an increase of 1.174 billion gallons ethanol and 1.92 million acres of land use
14-21 Emissions based on an increase of 0-15 billion gallons ethanol and 1.09-3.81 million acres of land use
22-49 Emissions based on an increase of ethanol production to meet EISA 2022 standards with a 30 year time horizon
Emissions based on an increase of 14.8 billion gallons ethanol and 26.7 million acres of land use
Tyner et al. 20103
EPA Modeling for EISA4 104 Searchinger et al. 20081 California (CARB) 20092
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grain exports, and therefore grain exports were held constant while biodiesel fuel was allowed to be imported from other states to meet the demand. To calculate the land required to produce biodiesel to import into the MN market, the same soybean and biodiesel yield rates were assumed for non-MN biodiesel production as in MN. The resulting change in crop production from 2010 to 2030 is shown in Table 7. The change in crop production is greater for the LCFS case than the reference scenario for MN corn and non-MN soybeans while the MN wheat and MN soybeans are the same. The change in land use is greatest for soybean production outside of MN due to unmet demand for biodiesel within the state.
To calculate the emissions that result from the land use change as a direct result of MN fuel policy, a total carbon release of 49 MgCO2e/acre was calculated based on work by
Hill et al. (2009), which assumes a total sequestration of 2.0 and 11.4 Mg/acre for root and soil sequestration respectively over a 50 yr span of prairie growth. As indicated in Table 7, the resulting emissions from land use are greater for the LCFS when compared to the reference due a larger number of acres in crop production. The emissions are compensated for by the lower cumulative emissions by the combustion of transportation fuels, which is lower for the LCFS than the reference scenario. The resulting total emission remain lower for LCFS policy scenario when compared to the reference scenario indicating that if land use change emissions are included within such a regulatory framework total transportation emissions can still be lowered. Table 7: Land use change emissions for the reference and low carbon fuel policy.
1 Data from Table B of agriculture study associated with this report.
2 Values calculated based on the agricultural model results shown in Table B which indicated that the 2030 MN imports of biodiesel will be 715 and 799 million liters for the reference and LCFS policy, respectively.
3 Data from Figure 18 of the policy report associated with this study.