44 Figure 4: TRACI characterized result global warming potential.

To further validate the models GHG result, the GHG value of corn ethanol derived from it are compared with other GHG findings from previous studies and models most commonly cited. In Figure 5, the mean value of four studies is 0.072 CO2-equivalents per MJ of corn ethanol supporting our result as in the reliable range of GHGs results.

Figure 5: Summary comparison of global warming potential of corn ethanol with other studies.

The variation arises from the difference in the defined system boundaries of the studies including upstream processes. For instance, the BESS model based on Liska’s research estimates lower life cycle GHG emissions for corn ethanol than does the widely-known GREET model. This

V-45

divergence is specifically derived from the two facts that the BESS model uses efficient bio- refinery and fails to properly include upstream emissions (Plevin, 2009).

Ozone Depletion

Results of running the modeling analytical framework indicates that the reduction in ozone depletion is the benefit of the two renewable fuels. Soybean has the lowest environmental impacts on ozone depletion. Soybean can reduce 75% of the total ozone depleting air emissions of conventional diesel. Corn ethanol has nearly 64% less air emissions than conventional gasoline. Even though the two renewable fuels increase ozone depletion caused by methane compounds (bromochlorodifluoro-, Halon 1211) emissions, they reduce methane compounds (bromotrifluoro-, Halon 1301) emissions that has twice as significant as Halon 1211. While Halon has been used for fire and explosion protection throughout the 20th _{century, the Montreal}

Protocol required that all production of ne Halon cease by January 1, 1994. Recycled Halon and inventories produced before 1994 are now the only sources of supply. Because of the phase out of Halon and the difficulty in estimating emissions from rate events, future research would be useful in furthering understanding of these relationships.

Figure 6: TRACI characterized result – ozone depletion.

Acidification

With regard to acidification potential, the two renewable fuels do not appear to fare well. The main contributors to the acidification impacts of all fuel pathways are ammonia (NH3), nitrogen

oxide (NOx), and sulfur dioxide (SO2). Corn ethanol has the highest acidification potential

followed by soybean diesel because more NH3, NOx, and SO2 emissions are liberated from corn

ethanol and soybean diesel conversion plants. Despite higher SO2 air emissions in conventional

fuels, corn ethanol and soybean diesel produce NH3 and NOx air emissions that have more

V-46

energy consumption for farming at crop cultivation and process energy consumption at bio- refinery.

As with results across all impact categories presented in this report, TRACI characterization factors for ozone depletion attempt to approximate total National deposition of expected H+ equivalents. Therefore, the higher lifetime ammonia and NOx emissions from corn ethanol are the main contributors to its higher acidification potential. However, it is important to note that the TRACI formulation estimates the total acidifying deposition potential and not actual harm. The sensitivity of soils and waters to acid deposition varies by location. These spatially specific differences can lead to vastly different characterized results. Future research examining the specific sensitivities of MN soils and waters to acid deposition, nitrate mobility and uptake is important to understanding local impact.

Figure 7: TRACI characterized result – acidification.

Acid rain is recognized as a significant concern. In general, high temperatures created by the combustion of petroleum because nitrogen gas in the surrounding air to oxidize, creating nitrous oxides. Nitrous oxides, along with sulfur dioxide from the sulfur in the oil, combine with water in the atmosphere to create acid rain. Acidification of oceans due to uptake of CO2 emissions by

water to form carbonic acid is also recognized as a significant concern. However, it is beyond the scope of this study to explore emission pathways incorporated in the TRACI tool which result in their characterization.

Eutrophication and Photochemical Oxidation

Based TRACI emissions characterization factors corn ethanol and soybean diesel tend to contribute more to eutrophication than conventional fuels. N-fertilizer use in energy crop

V-47

The difference between corn ethanol and soybean diesel is that corn ethanol requires much higher P-fertilizer than soybean cultivation.

Similar to other locally specific impacts, eutrophication is an issue for which the spatial

distribution of emissions is important since it is a threshold phenomenon, in which the sensitivity of receiving waters is important. Nutrient transport in the form of leaching or runoff can vary dramatically by region. The transport factors in TRACI estimate the fraction of a nutrient release that eventually reaches an aquatic ecosystem for which it is limiting. Therefore, this analysis serves as a screening tool and additional LCI and characterization efforts are needed to better estimate local specificity. Future research should attempt to incorporate recent data of nutrient levels in streams and groundwater to assess the variability of eutrophication effects regionally and within the state.

Use of TRACI emissions characterization factors also indicates that Nitrogen Oxides (NOx) emissions result in high photochemical oxidation potential for corn ethanol and soybean diesel. Smog (photochemical oxidation) has a major respiratory human health impact effect.

U.S EPA uses Community Multi-Scale Air Quality (CMAQ) model as a means to account for local ozone formation chemistry (EPA (o); EPA (p)). In some locations (generally rural areas where crops are grown) ozone formation chemistry is NOx-limited. VOC emissions do not affect ozone formation. However, in urban areas ozone formation chemistry is VOC-limited, and NOx emissions reduction can increase ozone formation (National Resource Council, 1991). Ozone in the lower atmosphere is created through complex chemical reactions involving volatile organic compounds and nitrogen oxides. If the ratio of ambient levels of VOC to NOx is high, ozone formation is said to be "NOx-limited," that is, at the margin ozone depends just on NOx emissions. If the VOC/NOx ratio is low, ozone formation is "VOC-limited" so that reducing NOx has little marginal effect (and may even increase ozone in the immediate vicinity of the sources). Recent evidence has led scientists to conclude that VOC emissions from both natural and man-made sources are higher than previously believed; this has raised estimates of

VOC/NOx ratios, so there is a renewed interest in control of NOx (National Research Council, 1991) (Small and Kazimi 1995). Hudman et al. (2007) modeled simulated summertime ozone concentrations associated with decreases in power plant and industry NOx emissions and report corresponding overall reductions in ozone formation. That said, even though the NOx emission reduction was largest in the Midwest during the years studied, the ozone decrease was greater in the southeast due to higher ozone production efficiency (OPE) per unit NOx. In addition, while urban areas are generally classified as being VOC-limited, recent research found that observed VOC/NOx ratios vary from urban area to urban area, within urban areas, and sometimes from hour to hour - suggesting that current emissions inventories may not be accurately capturing 03 production regimes (Baker and Carlton 2010). This same study predicts that urban areas will be more NOx-limited in the future. The result of this fundamental difference between VOC-limited and NOx-limited areas is that the spatial distribution of ozone reductions from VOC reductions is dramatically different from the spatial distribution of ozone reductions from NOx reductions (Huess, 2003; Sillman, 1999).

In contrast to EPA’s CMAQ model, TRACI characterization factors give equal credit to both VOC and NOx reductions at all locations. The development of the TRACI methodology for characterizing photochemical smog or ozone formation is described in Bare et al., 2002 and