Alcohol-to-jet (ATJ) is one of the technical feasible biofuel technologies. It produces jet fuel from sugary, starchy, and lignocellulosic biomass, such as sugarcane, corn grain, and switchgrass, via fermentation of sugars to ethanol or other alcohols. This study assesses the ATJ biofuel production pathway for these three biomass feedstocks, and advances existing techno-economic analyses of biofuels in three ways. First, we incorporate technical uncertainty for all by-products and co-products though statistical linkages between conversion efficiencies and input and output levels. Second, future price uncertainty is based on case-by-case time-series estimation, and a local sensitivity analysis is conducted with respect to each uncertain variable. Third, breakeven price distributions are developed to communicate the inherent uncertainty in breakeven price. This research also considers uncertainties in utility input requirements, fuel and by-product outputs, as well as price uncertainties for all major inputs, products, and co-products. All analyses are done from the perspective of a private firm. The stochastic dominance results of net present values (NPV) and breakeven price distributions show that sugarcane is the lowest cost feedstock over the entire range of uncertainty with the least risks, followed by corn grain and switchgrass, with the mean breakeven jet fuel prices being $0.96/L ($3.65/gal), $1.01/L ($3.84/gal), and $1.38/L ($5.21/gal), respectively. The variation of revenues from by-products in corn grain pathway can significantly impact its profitability. Sensitivity analyses show that technical uncertainty significantly impacts breakeven price and NPV distributions. Technical uncertainty is critical in determining the economic performance of the ATJ fuel pathway. Technical uncertainty needs to be considered in future economic analyses. The variation of revenues from by-products plays a significant role in profitability. With the distribution of breakeven prices, potential investors can apply whatever risk preferences they like to determine an appropriate bid or breakeven price that matches their risk profile.

The GTAP model has been used to estimate biofuel policy induced land use changes and consequent GHG emissions for more than a decade. This paper reviews the history of the model and database modifications and improvements that have occurred over that period. In particular, the paper covers in greater detail the move from the 2004 to the 2011 database, and the inclusion of cropland intensification in the modeling structure. The results show that all the changes in the global economy and agricultural sectors cause biofuels induced land use changes and associated emissions can be quite different using the 2011 database versus 2004. The results also demonstrate the importance of including land intensification in the analysis. The previous versions of GTAP and other similar models assumed that changes in harvested area equal changes in cropland area. However, FAO data demonstrate that it is not correct for several important world regions. The model now includes land intensification, and the resulting land use changes and emission values are lower as would be expected. Dedicated energy crops are not similar to the first generation feedstocks in the sense that they do not generate the level of market-mediated responses which we have seen in the first-generation feedstocks. The major market-mediated responses are reduced consumption, crop switching, changes in trade, changes in intensification, and forest or pasture conversion. These largely do not apply to dedicated energy corps. The land use emissions for cellulosic feedstocks depend on what we assume in the emissions factor model regarding soil carbon gained or lost in converting land to these feedstocks. We examined this important point for producing bio-gasoline from miscanthus. Much of the literature suggests miscanthus actually sequesters carbon, if grown on the existing active cropland or degraded land. We provide some illustrative estimates for possible assumptions. Finally, it is important to note the importance of the new results for the regulatory process. The current California Air Resources Board carbon scores for corn ethanol and soy biodiesel are 19.8 and 29.1, respectively (done with a model version that includes irrigation). The new model and database carbon scores are 12 and 18, respectively, for corn ethanol and soy biodiesel. Thus, the current estimates values are substantially less than the values currently being used for regulatory purposes.

Biofuels impact on global land use has been a controversial yet important topic. Up until recently, there has not been enough biofuels to have caused major land use change, so the evidence from actual global land use data has been scant. However, in the past decade, there have been 72 million hectares added to global crop cover. In this research we take advantage of this new data to calibrate the Global Trade Analysis Project (GTAP) model and parameters. We make two major changes. First, we calibrate the land transformation parameters (called constant elasticity of transformation, CET) to global regions so that the parameters better reflect the actual land cover change that has occurred. Second, we alter the land cover nesting structure. In the old GTAP model, cropland, pasture, and forest were all in the same nest suggesting, everything else being equal, that pasture or forest convert to cropland with equal ease and cost. However, we now take advantage of the fact that pasture converts to cropland at lower cost than forest. The paper provides the theoretical and empirical justification for these two model improvements. Then it re-evaluates the global land use impacts due to the USA ethanol program using the improved model tuned with actual observations. Finally, it shows that compared to the old model, the new model projects: (1) less expansion in global cropland due to ethanol expansion; (2) lower U.S. share in global cropland expansion; (3) and lower forest share in global cropland expansion.

This paper introduces biofuels sectors as energy inputs into the GTAP data base and to the production and consumption structures of the GTAP-Energy model developed by Burniaux and Truong (2002), and further modified by McDougall and Golub (2008). We also incorporate Agro-ecological Zones (AEZs) for each of the land using sectors in line with Lee et al. (2005). The GTAP-E model with biofuels and AEZs offers a useful framework for analyzing the growing importance of biofuels for global changes in crop production, utilization, commodity prices, factor use, trade, land use change etc. We begin by validating the model over the 2001-2006 period. We focus on six main drivers of the biofuel boom: the hike in crude oil prices, replacement of MTBE by ethanol as a gasoline additive in the US, and subsidies for ethanol and biodiesel in the US and EU. Using this historical simulation, we calibrate the key elasticities of energy substitution between biofuels and petroleum products in each region. With these parameter settings in place, the model does a reasonably good job of predicting the share of feedstock in biofuels and related sectors in accordance with the historical evidence between 2001 and 2006 in the three major biofuel producing regions: US, EU, and Brazil. The results from the historical simulation reveal an increased production of feedstock with the replacement of acreage under other agricultural crops. As expected, the trade balance in oil sector improves for all the oil exporting regions, but it deteriorates at the aggregate for the agricultural sectors.