III.C. Life Cycle Assessment of Biofuel Systems: Ethanol and Biodiesel

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 1 III.C. Life Cycle Assessment of Biofuel Systems: Ethanol and Biodiesel Seungdo Kim and Bruce E. Dale* *Corresponding author Seungdo Kim Institution: Michigan State University Position: Visiting associate professor Mailing address: Department of Chemical Engineering, Room 2527 Engineering Building, Michigan State University, East Lansing, MI 48824-1226 Phone number: 517-355-4621 Fax number: 517-432-1105 E-mail address: kimseun@msu.edu Bruce E. Dale Institution: Michigan State University Position: Professor Mailing address: Department of Chemical Engineering, Room 2527 Engineering Building, Michigan State University, East Lansing, MI 48824-1226 Phone number: 517-353-6777 Fax number: 517-432-1105 E-mail address: bdale@egr.msu.edu III.C. Abstract The environmental performance of biofuel systems are investigated through life cycle assessment. The biofuel systems include ethanol derived from different types of feedstock (i.e. corn grain, corn stover and switchgrass) and biodiesel derived from soybean oil. The system boundary is from cradle to grave, namely from biomass production through biorefinery to biofueled vehicle operation. Furthermore, petroleum oil fueled vehicle operations such as gasoline and diesel are also included in the system boundary to estimate the environmental benefits associated with the biofuel systems. The environmental performance of each system is evaluated as crude oil used, nonrenewable energy consumption, greenhouse gas emissions, photochemical smog formation, acidification, and eutrophication. Results show that the ethanol fuel systems offer environmental benefits in terms of crude oil used, decreased nonrenewable energy usage, and greenhouse gas emissions - but increase some of local environmental impacts (i.e. acidification and eutrophication). The lignocellulose based ethanol system is more favorable than the corn grain based ethanol system in terms of crude oil used, nonrenewable energy used, and greenhouse gas emissions - due to surplus energy exported from a lignocellulosic biorefinery. However, acidification and photochemical smog formation associated with ethanol derived from lignocellulosic biomass are larger than those of corn grain based ethanol due to nitrogen content in lignocellulosic biomass. The biodiesel fuel system also offers environmental credits in terms of crude oil used, nonrenewable energy, greenhouse gas

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 2 emissions, and some local environmental impacts (except for acidification). The environmental comparison between the ethanol and biodiesel systems greatly depends on the comparison basis chosen. There are two possible comparison bases: traveling distance-oriented and arable landoriented perspectives. In the arable land-oriented perspective the ethanol fuel system is more favorable than the biodiesel fuel system in terms of crude oil used, nonrenewable energy and greenhouse gas emissions, while the traveling distance-oriented analyses shows that the B100 fuel system is the most favorable in terms of nonrenewable energy and greenhouse gas emissions, due to no crude oil used in the vehicle operation. The arable land-oriented analyses are likely more relevant for the sustainability of land use. (biodiesel, ethanol, corn grain, corn stover, integrated biorefinery, life cycle assessment, soybean, switchgrass) III.C.1. Introduction Ethanol derived from biomass has the potential to be a renewable transportation fuel that can replace gasoline. Ethanol is currently used as liquid fuel in two ways: E10 (a mixture of 10 % ethanol and 90 % gasoline by volume) and E85 (a mixture of 85 % ethanol and 15 % gasoline by volume). Most ethanol in the United States is derived from Zea mays (corn) grain via dry milling or wet milling, and its annual production capacity is about 18 000 000 m 3 (http://www.ethanolrfa.org/index.shtml). More ethanol plants, which in total would add up to 8 000 000 m 3 yr -1, are under construction. The environmental performance of corn-based ethanol has recently been scrutinized in several studies (Farrell et al., 2006; Kim & Dale, 2005a; Kim & Dale, 2005b; Kim & Dale, 2002; Pimentel, 2002; Pimentel, 1991; Pimentel & Patzek, 2005; Shapouri et al., 2002; Shapouri et al., 1995; Wang, 2000; & Wang et al., 1999). Most such studies have concluded that ethanol derived from corn grain used as liquid fuel could displace gasoline used in the transportation sector and reduce greenhouse gas emissions. There is another popular environmental indicator - net energy balance, more specifically net nonrenewable energy balance, of corn-based ethanol. Most studies referred to above conclude that ethanol requires less nonrenewable energy than it offers. However, three studies by Pimentel (Pimentel, 2002; Pimentel, 1991; Pimentel & Patzek, 2005) have shown that the input energy for corn-based ethanol production is larger than the energy content of ethanol. This disagreement is attributable to differing data sets (including data sources and ages) and methodologies. Methodological differences include choices of the system boundaries and the allocation procedures. This study does not deal with the net energy balance because the net energy of ethanol derived from corn grain have been well covered in other studies (Farrell et al., 2006; Shapouri et al., 2002; Shapouri et al., 1995; Pimentel, 2002; Pimentel, 1991; Pimentel & Patzek, 2005). Furthermore, the net energy analyses presume that all BTU have equal utility, a highly doubtful premise. Lignocellulosic biomass is the largest potential feedstock for ethanol and includes materials such as agricultural residues (e.g. corn stover, crop straws and Saccharum (sugarcane bagasse), herbaceous crops (e.g. Medicago sativa (alfalfa), Panicum virgatum (switchgrass), short rotation woody crops, forestry wastes, wastepaper, and other wastes (Wyman, 1996). Corn stover refers to all of the above ground parts of the corn plant except the grain. Approximately equal masses

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 3 of stover and grain are produced. The National Renewable Energy Laboratory (NREL) (Sheehan et al., 2003) carried out a life cycle assessment study on corn stover-based ethanol production, and concluded that using corn stover-based ethanol as liquid fuel can also save nonrenewable energy consumption and reduce greenhouse gas emissions. A Canadian study (Spatari, 2005) found that ethanol derived from switchgrass as well as from corn stover can reduce greenhouse gas emissions as used as liquid fuel. In both studies, lignocellulosic biomass (e.g. corn stover or switchgrass) is treated by dilute sulfuric acid to convert cellulose and hemicellulose to soluble sugars, which are fermented to produce ethanol. Lignin-rich fermentation residues are utilized to generate electricity and steam. Although no commercial lignocellulosic biomass to ethanol industry exists, such an industry could have the potential to provide environmental benefits in several categories. However, collecting corn stover from soil may result in lowering soil organic carbon levels, and may also increase soil erosion (Mann et al. 2002). A model-based simulation of the agricultural production system by Kim & Dale (2005b) shows that corn stover removal could lower the accumulation rate of soil organic carbon but could decrease N 2 O (a potent greenhouse gas) emissions from the soil and inorganic nitrogen losses due to leaching. When the lignin content in corn stover is utilized to generate electricity and steam, the overall corn stover based ethanol production system could reduce fossil fuel use and greenhouse gas emissions, providing a good example of trade-offs between local concerns and national (or global) concerns when corn stover is utilized in biobased product systems. Sheehan and colleagues (1998) performed a life cycle inventory of biodiesel and petroleum diesel and concluded that biodiesel from Glycine max (soybean) could reduce consumption of petroleum and would also reduce carbon dioxide, carbon monoxide, particulate matter, and sulfur oxides emissions. However, biodiesel increases nitrogen oxides and hydrocarbon emissions compared to petroleum diesel. Life cycle assessment (LCA) is powerful tools to address the environmental performance of biobased product systems. LCA is a tool to compile the inputs/outputs associated with a product (or service) life cycle (i.e. from cradle to grave) and to calculate the environmental burdens resulting from these inputs/outputs. The International Organization for Standardization (ISO) has standardized LCA methodologies (ISO, 1997; ISO, 1998; ISO, 2000a; & ISO, 2000b). LCA has four phases: Goal and Scope Definition, Life Cycle Inventory Analysis, Life Cycle Impact Assessment, and Life Cycle Interpretation. The Goal and Scope Definition phase defines the objective and methods, which include function and functional unit of a product system, reference flow, system boundary, environmental impacts investigated in a decision making process, and so forth. Life Cycle Inventory Analysis is a phase of collecting inputs/outputs and environmental burdens associated with processes in the system boundary, and normalizing the environmental burdens to the reference flow defined in the goal and scope definition phase. Life Cycle Impact Assessment estimates the potential environmental impacts associated with the environmental burdens resulted from the inventory analysis. Life Cycle Interpretation is a phase of analyzing results from the inventory analysis and the impact assessment in order to reach conclusions and recommendations. This study investigates the environmental performance of two biofuel systems - ethanol derived from different types of biomass (corn grain, corn stover, switchgrass) and biodiesel derived from soybean oil. Furthermore, two biofuel systems (i.e. ethanol and biodiesel) are compared to

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 4 determine which system offers more environmental benefits. The environmental performance is measured in terms of crude oil used, nonrenewable energy, greenhouse gas emissions, acidification, eutrophication, and photochemical smog formation. This study also estimates the environmental performance of an integrated biorefinery, in which ethanol is derived from both starch and lignocellulosic biomass, and lignin-rich residues are utilized to generate electricity and steam. Thus, this study includes five case studies: corn based ethanol system, corn stover based ethanol system, switchgrass based ethanol, biodiesel system, and integrated biorefinery system. (biodiesel, corn grain, corn stover, ethanol, life cycle assessment, soybean, switchgrass) III.C.2. Methods The functional unit for each biofuel system, which is the primary basis in LCA studies, is defined as traveling distance driven by an E85 fueled vehicle for the ethanol fuel system and by a B20 fueled vehicle (a mixture of 20 % biodiesel and 80 % petroleum-based diesel by volume) for the biodiesel fuel system. The reference flow is defined as one km driven by a biofueled vehicle. E85 and B20 fuels are not currently widely used, but have potential for primary alternative fuels in the future. The system boundary includes biomass production, transportation of biomass, the biorefinery, transportation and distribution of biofuel, and biofueled vehicle operations (i.e. an E85 fueled vehicle or a B20 fueled vehicle). Three types of biorefineries are investigated in this study: corn grain dry milling, soybean crushing/ biodiesel production process (referred to as soybean biorefinery), and the lignocellulosic biorefinery, in which ethanol is produced from corn stover or switchgrass. All the biorefineries investigated here produce co-products. For example, corn dry milling produces ethanol and distillers dried grains and solubles (DDGS) that is used as animal feed. Products from a soybean biorefinery are biodiesel, glycerin, soapstock, and soybean meal (used as animal feed). Lignocellulosic biorefinery produces ethanol and generates electricity and steam, which are used within the biorefinery. To estimate the environmental performance associated with only the main function (biofuel), the environmental burdens of the overall system are properly assigned to each function delivered by a system. This procedure is called an allocation, and ISO 14000 standard series recommend the system expansion approach, in which alternative product systems for co-products are introduced to estimate the environmental burdens of the main function (ISO, 1998). An alternative product system for a co-product fulfills an equivalent function to its corresponding co-product and is replaced by its corresponding co-product. The alternative products for DDGS in dry milling are assumed to be both corn grain and soybean meal (Wang et al., 1999). Thus DDGS could replace corn grain and soybean meal with its appropriate fractions. It is assumed that the protein of soybean meal in the soybean biorefinery replace those of DDGS. Thus, the alternative product for soybean meal is DDGS (Kim & Dale, 2005b). Glycerin from the soybean biorefinery can replace conventional glycerin made from petroleum and natural gas (Morrison, 2000). Soapstock is not taken into account in the analysis due to its small quantity. Surplus electricity and steam from the lignocellulosic biorefinery are exported to replace electricity and steam generated by fossil energy. In this study, we assume that the alternative electricity is generated in a coal-fired power plant, and the alternative steam is

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 5 generated by fossil fuels (i.e. petroleum oil and natural gas). The alternative product systems are included in the system boundary. Petroleum oil fueled vehicle operations (e.g. gasoline and diesel) are also included in the system boundary to estimate the environmental benefits (or losses) associated with the biofuel system. It is assumed that ethanol is used as E85 fuel in a compact passenger vehicle and that biodiesel is used as B20 fuel in a transit bus (Lyons, 2002). The system boundary is illustrated in figure 1. <Figure 1> In the case of ethanol derived from corn stover, the environmental burdens associated with biomass production (corn cultivation with collecting corn stover) should be assigned to corn grain and corn stover to estimate the environmental burdens solely associated with corn stover. The allocation between corn grain and corn stover is done by subtracting the environmental burdens of corn grain from the overall environmental burdens. The environmental burdens of corn grain are estimated from the corn grain based ethanol system, in which only corn grain is harvested. Therefore the environmental burdens associated with corn stover account for changes due to collecting corn stover from the field such as changes in soil organic carbon levels, nitrogen related emissions from soil, fuel consumption in harvesting and baling corn stover, and additional nutrient requirements in the subsequent growing season. The environmental burdens associated with the field operations (e.g., tillage, application, harvesting corn grain, etc.) are assigned to corn grain. This allocation procedure is equivalent to the system expansion approach. The cropping sites are specified because soil organic carbon levels and emissions from soil (e.g. N 2 O, NOx, NO 3 -, etc.) vary with soil properties, climate, cropping management and so forth. Hardin County and its adjacent counties (Franklin, Grundy, Hamilton, Jasper, Marshall, Story and Tama) in Iowa are considered for modeling in this study. Hardin County has a corn dry mill and a soybean crushing plant. The fraction of biomass supplied from each county to biorefineries is based on total corn (or soybean) production. Yields for corn and soybean in Hardin County and its adjacent counties are available at the National Agricultural Statistics Service (NASS) (http://www.usda.gov/nass/pubs/estindx1.htm#agchem). The agronomic inputs (fertilizers, herbicides, pesticides and lime) are also available at the NASS. However, the state-based values are used in the agronomic inputs instead of county-based values due to lack of county specific data. This study uses four-year average values over year 2001 through year 2003 for corn yield and agronomic inputs. State-level fuel consumption, which is based on the year 2001, is available at the Economic Research Service (http://www.ers.usda.gov/data/costsandreturns/testpick.htm). There is no information on county-based fuel consumption. State-level information on switchgrass cultivation is obtained from a previous study (Kim & Dale, 2004). It is assumed that only 50 % of the corn stover is collected for feedstock into the lignocellulosic biorefinery to keep soil erosion at the tolerable levels (Nelson, 2002). Nutrient losses due to collecting corn stover in the subsequent growing season are taken into account in the application rates of fertilizers (i.e. nitrogen, phosphorus, potassium). The tillage practices for

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 6 all the cultivations are assumed to be no-tillage practice. The transportation of biomass to the biorefinery consists of two parts: internal transportation and inter-county transportation. Traveling distance in the internal transportation is estimated by the approximate radius of the county. Traveling distance in inter-county transportation, from the adjacent counties to Hardin County, is assumed to be the distance between the locations of each county city. Soil organic carbon dynamics, inorganic nitrate losses due to leaching, and nitrous oxide and nitrogen oxide emissions from soil in each county are simulated by the DAYCENT model, which is the daily time step version of the CENTURY model, a multicompartmental ecosystem model (Del Grosso et al., 2001; Del Grosso et al., 2000; & Natural Resource Ecology Laboratory, 2005). The CENTURY model simulates the long-term dynamics of carbon, nitrogen and other substances for different ecosystems (e.g. agricultural crop system, grass system, etc.) and is adequate for simulation of medium- and long-term (100 to >1000 yrs) changes in soil organic carbon and other ecosystem parameters in response to changes in climate, land use, and management. The trace gas submodel of the DAYCENT model simulates N 2 O, NOx and N 2 emissions from soil resulting from nitrification and denitrification. Required input parameters for the model include climate information (temperature and precipitation), site-specific soil properties (soil texture, soil organic content, soil moisture content, and soil mineral content), and the current and historical cropping system. Corn grain is assumed to be converted into ethanol via corn dry milling, in which ethanol yield is 0.32 kg ethanol/kg of dry corn grain (McAloon et al., 2000). The process data for the lignocellulosic biorefinery, in which the ammonia fiber expansion (AFEX) process is used as a pretreatment, are estimated from the ASPEN PLUS models, developed by Laser and Lynd (2005). Ethanol yield in the lignocellulosic biorefinery is assumed to be 0.34 (0.32) kg ethanol/kg of dry corn stover (kg of dry switchgrass) (Wu et al., 2006). Ethanol yield in the lignocellulosic biorefinery reflects the future scenario, not the current case. A sensitivity analysis investigates the effects of ethanol yield in the overall environmental performance of the ethanol fuel system. Lignin-rich residues and biogas from wastewater treatment facility in the lignocellulosic biorefinery are assumed to be utilized to generate electricity and steam. The information on generation efficiency for electricity and steam is available from a government report (Aden et al., 2002). It is assumed that surplus electricity and steam are exported to electricity grid and to district heating system, respectively. One kg of biodiesel is produced from 1.04 kg of soybean oil (Sheehan et al., 1998). Some of tailpipe emissions from driving vehicles are also available from a previous study (Kim & Dale, 2005b; Kim & Dale, 2006). Other data sources are summarized in table 1. <Table 1> The greenhouse gases (GHG) include carbon dioxide, methane, nitrous oxide (N 2 O) and other greenhouse gases. The GHG evaluation also includes carbon sequestration due to increasing soil organic carbon and N 2 O releases from the soil during cultivation. Carbon contents in biomass, other co-products and biofuels are not accounted for in this study because these carbon contents are eventually released into the air. The 100-year time horizon global warming potentials (Intergovernmental Panel on Climate Change, 2001) are used to estimate global warming impact. The characterization factors for local environmental impacts (e.g. acidification, eutrophication

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 7 and photochemical smog formation) are adapted from the TRACI model (Tools for the Reduction and Assessment of Chemical and Other Environmental Impacts) developed by the United States Environmental Protection Agency (Bare, 2003). (allocation, data sources, DAYCENT model, functional unit, life cycle assessment, potential environmental impact categories, system boundary) III.C.3. Results III.C.3.a. Ethanol from corn grain The environmental performance of the corn grain based ethanol fuel system is summarized in table 2. The biomass production column in table 2 includes corn grain production and transportation of corn grain from the farm to the dry mill. The biorefinery column represents processes including the dry milling process and alternative product system for DDGS. Vehicle operation includes transportation of ethanol to retailers, E85 fueled vehicle operation, and alternative production system (i.e. gasoline fueled vehicle operation). Driving one km consumes 86.4 g of ethanol and 14.2 g of gasoline for an E85 fueled compact passenger vehicle, and 73.3 g of gasoline for a gasoline fueled compact passenger vehicle. <Table 2> Using ethanol derived from corn grain as an E85 fuel offers crude oil credit (60.9 g km -1 ), nonrenewable energy credit (1.5 MJ km -1 ), and GHG credits (122 g CO 2 eq. km -1 ). The crude oil credit in the biorefinery is due to the alternative product systems for DDGS (i.e. corn grain and soybean meal). The biorefinery consumes more nonrenewable energy than corn grain production because the dry milling process is energy-intensive. There are no greenhouse gas credits in the biomass production and biorefinery. N 2 O from soil is the primary greenhouse gas in biomass production, while CO 2 associated with process energy (i.e. electricity, steam and natural gas) is the primary greenhouse gas in the biorefinery. A large greenhouse gas credit occurs in the vehicle operation subsystem because CO 2 emissions from combusting ethanol in E85 fuel are not taken in account as greenhouse gas emissions because carbon dioxide from the atmosphere is absorbed by plants during growing season. Thus using ethanol as E85 fuel in a compact passenger vehicle would reduce overall greenhouse gas emissions. The corn grain based ethanol fuel system also offers photochemical smog formation credit. Most photochemical smog formation benefits are associated with the alternative product system for DDGS, particularly corn grain. The corn grain based ethanol fuel system increases acidification and eutrophication more than the gasoline fuel system. NOx emissions from soil during corn cultivation are the primary emissions in acidification and eutrophication, and phosphorus losses from phosphorus fertilizer are also the primary emissions in eutrophication. (corn grain, ethanol)

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 8 III.C.3.b. Ethanol from corn stover The environmental performance of corn stover based ethanol fuel system is summarized in table 3. Biomass production in table 3 includes corn stover production and transportation of corn stover farm to the lignocellulosic biorefinery. The environmental burdens associated with corn stover production are the sum of the environmental burdens of harvesting corn stover, and additional fertilizer requirements in the subsequent growing season and changes in soil emissions (e.g. changes of soil organic carbon level, N 2 O, NOx and NO 3 - ) due to removing corn stover from soil. The biorefinery represents processes including lignocellulosic biorefinery and alternative product systems for electricity and steam exported. The lignocellulosic biorefinery generates 0.25 MJ of electricity km -1 and 0.86 MJ of steam km -1 from fermentation residues and biogas from the wastewater treatment facility with energy value of 1.69 MJ km -1, and exports 0.09 MJ of electricity km -1 and 0.34 MJ of steam km -1. <Table 3> The E85 fuel derived from corn stover offers environmental benefits in terms of crude oil, nonrenewable energy, and GHG. Corn stover based ethanol provides more credits per km than corn grain based ethanol because of surplus electricity and steam from the lignocellulosic biorefinery exported. The corn stover based ethanol fuel system could save crude oil by 65 g km -1 and reduce greenhouse gas by 245.5 g CO 2 eq. km -1, which is almost twice as large as in corn grain based ethanol fuel system even though removing corn stover from the soil decreases soil organic carbon level. The primary reasons for more greenhouse gas credits in the corn stover based ethanol system are the reduction in N 2 O emissions from soil due to removing corn stover from the field and the export of surplus energy (i.e. electricity and steam) from the lignocellulosic biorefinery. Eutrophication associated with the corn stover based ethanol fuel system is less than that of the corn grain ethanol system because of lower NO 3 - and phosphorus leaching in corn stover production. However, acidification and photochemical smog formation of the corn stover based ethanol fuel system are larger than those of the corn grain based ethanol fuel system even though removing corn stover from the soil reduces nitrogen related emissions from soil. As seen in tables 2 and 3, the big differences in these two local impacts between the two systems occur in the biorefinery. Nitrogen contents in corn stover are converted into NOx when utilizing ligninrich residues and biogas in the lignocellulosic biorefinery to generate electricity and steam. Obviously, these compounds could be removed from the air emissions and thus reduce the corresponding impacts but the inputs required to achieve such reductions are not known. (Corn stover, ethanol) III.C.3.c. Ethanol from switchgrass The switchgrass based ethanol fuel system can save nonrenewable energy and crude oil at the rates of 4.3 MJ km -1 and 68.5 g km -1, respectively. Using ethanol derived from switchgrass lowers greenhouse gases by 336 g km -1 driven by an E85 fueled vehicle, compared to a gasoline fueled vehicle operation. The switchgrass based ethanol fuel system offers more environmental credits than the corn stover based ethanol fuel systems in terms of crude oil, nonrenewable energy and greenhouse gas emissions. The greenhouse gas emission credit in biomass production is due to carbon sequestered by soil. Compared to corn stover based ethanol, the switchgrass based ethanol fuel system exports more

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 9 electricity and steam because of the assumption that switchgrass has more lignin than corn stover (Thammasouk et al., 1997). It is obvious that more lignin-rich biomass offers more environmental benefits in crude oil, energy and greenhouse gas emissions. Eutrophication of the switchgrass based ethanol system is higher than that of the corn stover based ethanol system due to high nitrogen fertilizer requirement in switchgrass cultivation. Other local environmental impacts of switchgrass based ethanol are similar to those of corn stover based ethanol. The environmental performance of the switchgrass based ethanol fuel system is summarized in table 4. The switchgrass based lignocellulosic biorefinery generates 0.33MJ of electricity km -1 and 1.15 MJ of steam km -1 from fermentation residues and biogas from wastewater treatment facility with energy value of 2.25 MJ km -1, and exports 0.16 MJ of electricity km -1 and 0.59 MJ of steam km -1. <Table 4> (ethanol, switchgrass) III.C.3.d. Sensitivity analysis Lower ethanol yield, which would reflect the current situations, is considered in the sensitivity analysis: 0.23 kg ethanol/kg of dry corn stover and 0.22 kg of dry switchgrass. Results show that more energy is exported from the lignocellulosic biorefinery at a lower ethanol yield in the lignocellulosic biorefinery because more materials are available for generating electricity and steam energy even though lower ethanol yield increases process energy by about 15 %. A lower ethanol yield offers more environmental benefits than a higher ethanol yield in terms of crude oil, energy and greenhouse gas emissions, while local environmental impacts associated with the ethanol system at a lower yield are larger than those at a high yield (see figures 2-3). The sensitivity analyses show that a lower ethanol yield offers more environmental benefits in some environmental impacts than a higher yield. However, a lower ethanol yield would not offer better performance in terms of economic and social aspects. <figure 2> <figure 3> (corn stover, ethanol, sensitivity analysis, switchgrass, yield) III.C.3.e. Biodiesel The environmental performance of the biodiesel fuel system is summarized in table 5. The biodiesel fuel system offers environmental credits in terms of crude oil, nonrenewable energy and greenhouse gas emissions as well. Furthermore, eutrophication and photochemical smog formation associated with the biodiesel fuel system are less than those of the diesel fuel system because of large environmental credits from the alternative product systems for soybean meal and vehicle operations. The soybean biorefinery provides environmental credits in all the environmental impacts considered here because DDGS production, which is the alternative product system for soybean meal, has large offsetting effects. <Table 5>

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 10 (biodiesel, soybean) III.C.3.f. Comparison It is obvious that the results from the ethanol system can not directly be compared to those from the biodiesel system presented in the last section because of different functions delivered by two systems: one for a compact passenger vehicle and another for a bus. Thus, comparisons of two systems should be based on an equivalent function such as distance driven by a same size vehicle or arable land (Kim & Dale, 2006). Some information on passenger vehicles driven by diesel or biodiesel is available from a website of the Office of Energy Efficiency and Renewable Energy (http://www.fueleconomy.gov/), but their tailpipe emission data are not complete. Only fuel economies for diesel fueled vehicles are available, which are enough to estimate crude oil used, energy and greenhouse gas emissions. The local impacts associated with the biodiesel fuel system for passenger vehicles therefore can not be estimated at this time. That is a reason that these vehicles are excluded in the full analyses. It is assumed that B100 fuel (pure biodiesel) and B20 fuel reduce the fuel economy of a diesel fueled vehicle by 10 % and 2 %, respectively (http://www.fueleconomy.gov/). The comparisons of biofuel systems (i.e. ethanol and biodiesel) are done with two different bases: traveling distance-oriented and arable land-oriented perspectives (Kim & Dale, 2006). The traveling distance-oriented analyses imply that the supply of biofuel is not constrained, while the supply of biofuel in the arable land-oriented analyses is constrained due to the limitation in the availability of arable land for biofuel. Thus, the traveling distance-oriented analyses are more relevant in a case that the supply is greater than the demand. The arable land-oriented analyses indicate that demand for biofuel is greater than supply which seems far more reasonable. Results from the comparisons are illustrated in figures 4-5, in which the Y axes represent relative environmental credits that are estimated from dividing the credits associated with each system by the credits of the corn grain based ethanol system. As mentioned previously, the ethanol fuel systems derived from lignocellulosic biorefineries in the comparisons reflect future technologies rather than current technologies. In the traveling distance-oriented analyses, the B100 fuel system offers the largest environmental credits among other systems in terms of nonrenewable energy and greenhouse gas emissions because a B100 fueled vehicle does not use any diesel in the vehicle operation. The switchgrass based ethanol system is the most favorable in crude oil used. The corn grain based ethanol system has the poorest environmental performance among other systems considered in this study in crude oil, nonrenewable energy and greenhouse gas emissions. The results from the traveling distance-oriented analyses show that biodiesel could reduce nonrenewable energy and greenhouse gas emission more than ethanol only if it is used as B100 fuel. <Figure 4> <Figure 5> Results from the arable land-oriented analyses are quite different from findings in the traveling distance-oriented analyses. In the arable land-oriented analyses, ethanol offers much more environmental credits than the biodiesel systems in terms of crude oil, nonrenewable energy and greenhouse gas emissions. The primary reason is biomass yield. The yield of soybean is much lower than that of corn grain or of switchgrass. From the sustainability viewpoint on arable land

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 11 efficiency, the arable land-oriented perspective is more relevant. For the local environmental impacts, more information is required to determine which system is more environmentally friendly. (arable land-oriented perspectives, traveling distance-oriented perspectives) III.C.3.g. Integrated biorefinery An integrated biorefinery is defined as a biorefinery in which biobased products are produced from both lignocellulosic and starch biomass. One of the merits associated with an integrated biorefinery is that the starch based biorefining processes can utilize surplus energy generated in the lignocellulosic biorefinery process, in which fermentation residues and biogas from wastewater treatment are used as fuel sources to generate both electricity and steam. Thus an integrated biorefinery has the potential to reduce the energy consumption in the starch based biorefinery. Currently no commercial lignocellulosic biorefinery exists, so it is likely that new lignocellulosic biorefineries will be built within existing dry (or wet) milling plants. We assume that the annual production rate of an integrated biorefinery considered in the analysis is 90 000 m 3 yr -1 for corn grain based ethanol and 640 000 m 3 yr -1 for lignocellulose based ethanol (i.e. corn stover or switchgrass), which are based on the Aspen Plus model from the other studies (McAloon et al., 2000; Laser & Lynd, 2005). Ethanol produced in the integrated biorefinery offers better environmental performance than corn grain based ethanol in terms of most environmental impacts considered here except for acidification and photochemical smog formation (see table 6) due to utilization of the surplus energy from the lignocellulosic biorefinery process, which replaces fossil energy used in the dry milling process. The main reason for poor performance in acidification and photochemical smog formation associated with ethanol from an integrated biorefinery is the nitrogen content in lignocellulosic biomass, which is assumed to be converted into NOx in the combustion process. Integrated biorefinery B, in which ethanol is produced from both corn grain and switchgrass, is slightly more favorable in crude oil, nonrenewable energy and greenhouse gas emissions than integrated biorefinery A (corn grain and corn stover as feedstock). As mention previously, this is due to higher lignin content in switchgrass. Integrated biorefinery A, in which corn stover is used as feedstock for lignocellulosic biomass, offers the lowest eutrophication impact among others because removing corn stover reduces nitrogen related emissions from soil, and corn stover production requires smaller phosphorus fertilizer, which is only additional nutrient required in the subsequent growing season. <Table 6> Effects of the environmental impacts associated with an integrated biorefinery with respect to changing the production capacity of lignocellulose based ethanol would offer environmental guidelines to determine the production capacities in an integrated biorefinery (see fig. 6). The production capacity of lignocellulose based ethanol changes from 85 % to 120 % of the reference case (640 000 m 3 yr -1 ), while the production capacity of corn grain based ethanol remains unchanged. Increasing the production capacity of lignocellulose based ethanol reduces crude oil used, nonrenewable energy and greenhouse gas emissions. However, local impacts have opposite

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 12 effects except for eutrophication of integrated biorefinery A. The opposite effects in acidification, photochemical smog formation, and eutrophication in integrated biorefinery B are due to nitrogen contents in lignocellulosic biomass, which are converted into NOx in the combustion process. Thus, increasing the production capacity of lignocellulose based ethanol increases the local environmental impacts except for eutrophication of integrated biorefinery A. Increasing the production rate of corn stover based ethanol in integrated biorefinery A reduces NO 3 - leaching and phosphorus losses in corn stover production and then decreases the overall eutrophication associated with the ethanol fuel system. <Figure 4> (ethanol, integrated biorefinery) III.C.4. Conclusion Biofuel systems (i.e. ethanol and biodiesel) can save crude oil, reduce nonrenewable energy consumption and lower greenhouse gas emissions regardless of the types of biomass investigated in this study. The corn grain based ethanol system offers photochemical smog formation benefit but increases other local environmental impacts. The biodiesel fuel system also offers environmental benefits in terms of eutrophication and photochemical smog formation due to the environmental credits from the alternative product systems for soybean meal and vehicle operations. However, the local impacts associated with the lignocellulose based ethanol, such as acidification, eutrophication and photochemical smog formation, are greater than those of the gasoline fuel system. Therefore, there are no local environmental benefits in most ethanol fuel system particularly because of nitrogen and phosphorus losses in biomass production and the nitrogen contents in lignocellulosic biomass, which are converted into NOx in the combustion process. Biorefinery emissions can presumably be reduced at a price. Ethanol derived from lignocellulosic biomass (i.e. corn stover and switchgrass) has environmental advantages over corn grain based ethanol in terms of crude oil, nonrenewable energy and greenhouse gas emissions due to surplus energy exported from the lignocellulosic biorefinery. However, acidification and photochemical smog formation associated with lignocellulose based ethanol system are larger than those of corn grain based ethanol fuel system because of the protein content in lignocellulosic biomass. It is possible to recover protein from lignocellulosic biomass in the lignocellulosic biorefinery. Since these technologies would require energy to recover protein from lignocellulosic biomass, without detailed information it can not be said that adding a protein recovery process into a lignocellulosic biorefinery would always offer more environmental benefits than a non-protein recovery lignocellulosic biorefinery in terms of all the environmental impacts. To determine the environmental performance, a detailed life cycle assessment is needed in the future. It is shown that the lignin content in lignocellulosic biomass is one of the primary factors to determine the environmental performance of the lignocellulose based ethanol fuel system. Higher lignin contents generate more energy that is used within the biorefinery processes and exported, which reduces most environmental impacts. Integrated biorefinery technologies can

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 13 reduce some of environmental impacts associated with corn grain based ethanol production due to energy generated from lignocellulosic biorefinery. In the traveling distance-oriented analyses, the B100 fuel system is the most favorable in terms of nonrenewable energy and greenhouse gas emissions due to almost no crude oil used in the vehicle operation. However, in the arable land-oriented analyses, the ethanol fuel system is more favorable than the biodiesel fuel system in terms of crude oil used, nonrenewable energy and greenhouse gas emissions. The arable land-oriented analyses would be likely more relevant for sustainability of land use. (acidification, biofuel, crude oil, eutrophication, greenhouse gas emissions, nonrenewable energy, photochemical smog formation) Acknowledgements The authors gratefully acknowledge support provided by DuPont Biobased Materials, Inc. (Wilmington, Delaware, USA), by the National Science Foundation (Project No.: DMII- PREMISE-II #: 0400296) and by United States Department of Energy (Project No.: DE-FG36-04Go14220). References Aden, M.; Ruth, K.; & Ibsen, J. [et al.] (2002). Lignocellulosic Biomass to Ethanol Process Design and Economics Utilizing Co-Current Dilute Acid Prehydrolysis and Enzymatic Hydrolysis For Corn Stover. (NREL/TP-510-32438). National Renewable Energy Laboratory. Bare, J. (2003). Tools for the Reduction and Assessment of Chemical and Other Environmental Impacts (TRACI): User's Guide and System Documentation. (EPA/600/R-02/052). United States Environmental Protection Agency. Del Grosso, S.J.; Parton, W.J.; & Mosier, A.R. [et al.] (2001). Simulated interaction of carbon dynamics and nitrogen trace gas fluxes using the DAYCENT model. In Modeling carbon and nitrogen dynamics for soil management (pp. 303 332). Boca Raton, FL: Lewis Publishers. Del Grosso, S.J.; Parton, W.J.; & Mosier, A.R. [et al.] (2000). General model for N 2 O and N 2 gas emissions from soils due to denitrification. Global biogeochemical cycles, 14, 1045 1060. Ecobilan. TEAM TM LCA database. France. Farrell, A.E.; Plevin, R.J.; & Turner, B.T. [et al.] (2006). Ethanol can contribute to energy and environmental goals. Science, 311, 506 508. Intergovernmental Panel on Climate Change (IPCC) (2001). Climate change 2001: the scientific basis. Cambridge, UK: Cambridge University Press.

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 14 International Fertilizer Industry Association (IFA) (2006). Nitrogen, phosphate and potash statistics from 1973/74 to 2003/2004. Retrieved July 10, 2006, from http://www.fertilizer.org/ifa/statistics/ifadata/summary.asp International Fertilizer Industry Association (IFA) (1998). Mineral fertilizer production and the environment. Part 1. The fertilizer industry's manufacturing processes and environmental issues. (Technical report NO.26 PART 1). IFA/UNEP/UNIDO. International Organization for Standardization (ISO) (1997). International organization for standardization 14040: Environmental management Life cycle assessment principles and framework. International Organization for Standardization. International Organization for Standardization (ISO) (1998). International organization for standardization 14041: Environmental management Life cycle assessment Goal and scope definition and inventory analysis. International Organization for Standardization. International Organization for Standardization (ISO) (2000a). International organization for standardization 14042: Environmental management Life cycle assessment Life cycle impact assessment. International Organization for Standardization. International Organization for Standardization (ISO) (2000b). International organization for Standardization 14043: Environmental management Life cycle assessment Life cycle interpretation. International Organization for Standardization. Kim, S.; & Overcash, M. (2000). Allocation procedure in multi output process an illustration of ISO 14041. International Journal of Life Cycle Assessment, 5, 221 228. Kim, S.; & Dale, B.E. (2002). Allocation procedure in ethanol production system from corn grain: I. system expansion. International Journal of Life Cycle Assessment, 7, 237 243 Kim, S.; & Dale, B.E. (2004). Cumulative energy and global warming impact associated with producing biomass for biobased industrial products, Journal of Industrial Ecology. 7, 147 162. Kim, S.; & Dale, B.E. (2005a). Environmental aspects of ethanol derived from no-tilled corn grain: nonrenewable energy consumption and greenhouse gas emission. Biomass & Bioenergy, 28, 475 489. Kim, S.; & Dale, B.E. (2005b). Life cycle assessment of various cropping systems utilized for producing biofuels: bioethanol and biodiesel. Biomass & Bioenergy, 29, 426 439. Kim, S.; & Dale, B.E. (2005c). Life cycle inventory information of the United States electricity system. International Journal of Life Cycle Assessment, 10, 294 304. Kim, S.; & Dale, B.E. (2006). Ethanol Fuels: E10 or E85 Life Cycle Perspectives. International Journal of Life Cycle Assessment, 11, 117 121.

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 15 Laser, M.; & Lynd, R.L., personal communications. May, 2005. Lyons, D.W. (2002). Biodiesel fuel comparison final data report. West Virginia University. Retrieved July 10, 2006, from http://www.afdc.doe.gov/pdfs/wvu_biodiesel_report.pdf Mann, L.; Tolbert, V.; & Cushman, J. (2002). Potential environmental effects of corn (Zea mays L.) stover removal with emphasis on soil organic matter and erosion. Agriculture, Ecosystems and Environment, 89, 149-166. McAloon, A.; Taylor, F.; & Yee, W. [et al.] (2000). Determining the cost of producing ethanol from corn starch and lignocellulosic feedstocks. (NREL/TP-580-28893). National Renewable Energy Laboratory. Morrison, L.R. (2000). Glycerol, Kirk-Othmer Encyclopedia of Chemical Technology, John Wiley & Sons, Inc. Retrieved Jun 12, 2006, from http://www.mrw.interscience.wiley.com/kirk/articles/glycmorr.a01/pdf_fs.html Natural Resource Ecology Laboratory (2005). Century soil organic matter model: user's guide and reference. Colorado State University. Retrieved July 9, 2006, from http://www.nrel.colostate.edu/projects/century5/reference/index.htm Nelson, R.G. (2002). Resource assessment and removal analysis for corn stover and wheat straw in the Eastern and Midwestern United States - rainfall and wind erosion methodology. Biomass and Bioenergy, 22, 349-363. Office of Industrial Technologies (2000). Energy and environmental profile of the U.S. chemical industry. United States Department of Energy. Retrieved June 1, 2006, from http://www.eere.energy.gov/industry/chemicals/pdfs/profile_chap1.pdf#search=%22%22ene rgy%20and%20environmental%20profile%20of%20the%20u.s.%20chemical%20industry% 22%22 Overcash, M. (2000). Gate to gate life cycle information of glycerine. North Carolina State University. Pagani, G.; & Zardi, U. (1994). Process and plant for the production of urea. US Patent. 5,276,183. Pimentel, D.; & Patzek, T.W. (2005). Ethanol Production Using Corn, Switchgrass, and Wood; Biodiesel Production Using Soybean and Sunflower. Natural Resources Research. 14, 65 76. Pimentel, D. (1991). Ethanol fuels: Energy security, economics, and the environment. Journal of Agricultural Environmental Ethics. 4, 1-13.

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 16 Pimentel, D. (2002). Limits of biomass utilization. In Encyclopedia of physical science and technology (pp. 159 171). New York, NY: Academic Press. Shapouri, H.; Duffield, J.A.; & Graboski, M.S. (1995). Estimating the net energy balance of corn ethanol. (Agricultural Economic Report 721). US Department of Agriculture. Shapouri, H.; Duffield, J.A.; Wang, M. (2002). The energy balance of corn ethanol: An update. (Agricultural Economic Report 813)., US Department of Agriculture. Shapouri, H.; & Paul, G. (2005). USDA s 2002 Ethanol cost-of-production survey. (Agricultural Economic Report 841). US Department of Agriculture. Sheehan, J.; Aden, A.; & Paustian, K. [et al.] (2003). Energy and Environmental Aspects of Using Corn Stover for Fuel Ethanol, Journal of Industrial Ecology, 7, 117-146. Sheehan, J.; Camobreco, V.; & Duffield, J. [et al.] (1998). Life cycle inventory of biodiesel and petroleum diesel for use in an urban bus. (NREL/SR-580-24089). National Renewable Energy Laboratory. Spatari, S; Zhang, Y.M.; & MacLean, H.L. (2005). Life cycle assessment of switchgrass- and corn stover-derived ethanol-fueled automobiles. Environmental Science & Technology, 39, 9750-9758. Thammasouk, K.; Tandjo, D.; & Penner, M.H. (1997). Influence of extractives on the analysis of herbaceous biomass, Journal of Agricultural and Food Chemistry, 45, 437-443. Wang, M. (2000). Greet 1.5a Transportation fuel-cycle model. Argonne National Laboratory. Wang, M.; Saricks, C.; & Santini, D. (1999). Effects of fuel ethanol use on fuel-cycle energy and greenhouse gas emissions. *ANL/ESD-38). Argonne National Laboratory. Wu, M.; Wu, Y.; & Wang, M. (2006). Energy and Emission Benefits of Alternative Transportation Liquid Fuels Derived from Switchgrass: A Fuel Life Cycle Assessment, Biotechnology Progress, 22, 1012-1024. Wyman, C.E. (1996). Ethanol production from lignocellulosic biomass: overview. In Handbook on bioethanol: production and utilization (pp. 1-18). Washington DC: Taylor & Francis.

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 17 Table 1 Primary data sources List of Captions for Tables Table 2 Environmental performance of the corn grain based ethanol fuel system Table 3 Environmental performance of the corn stover based ethanol fuel system Table 4 Environmental performance of the switchgrass based ethanol fuel system Table 5 Environmental performance of the biodiesel fuel system Table 6 Environmental performance of an integrated biorefinery Figure 1 System boundaries List of Legends for Figures Figure 2 Effect of ethanol yield on the ethanol derived from corn stover system [Current yield: 0.23 kg ethanol/kg of dry corn stover; Future yield: 0.34 kg ethanol/kg of dry corn stover; Energy: nonrenewable energy; GHG: greenhouse gas emissions; Acid.: acidification; Eutro.: eutrophication; Smog: photochemical smog formation] Figure 3 Effect of ethanol yield on the ethanol derived from switchgrass system [Current yield: 0.22 kg ethanol/kg of dry corn stover; Future yield: 0.32 kg ethanol/kg of dry corn stover; Energy: nonrenewable energy; GHG: greenhouse gas emissions; Acid.: acidification; Eutro.: eutrophication; Smog: photochemical smog formation] Figure 4 Traveling distance-oriented analyses for the relative environmental credits associated various biofuel systems. The environmental credit of the corn grain based ethanol system is the basis case. Figure 5 Arable land-oriented analyses for the relative environmental credits associated various biofuel systems. The environmental credit of the corn grain based ethanol system is the base case. Figure 6 Effects of changing the production capacity of lignocellulose based ethanol in the integrated biorefinery. Red lines represented integrated biorefinery A, and blue lines represented integrated biorefinery B. [Energy: nonrenewable energy; GHG: greenhouse gas emissions; Acid.: acidification; Eutro.: eutrophication; Smog: photochemical smog formation]

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 18 Table 1 Primary data sources Process References Agronomic inputs for corn and soybean cultures National Agricultural Statistics Service (http://www.usda.gov/nass/pubs/estindx1.htm#agchem) Fuel consumption in corn and soybean cultures Economic Research Service (http://www.ers.usda.gov/data/costsandreturns/testpick.htm) Switchgrass culture Kim and Dale (2004) Climate and soil data in the cropping site NSSC Soil Survey Laboratory Soil Characterization Data (http://ssldata.nrcs.usda.gov/querypage.asp?chksa=1&ac=244& as=3951#sitevar) National Climatic Data Center (http://lwf.ncdc.noaa.gov/oa/climate/stationlocator.html) Fuel consumption for harvesting corn stover Sheehan et al. (2002) Dry milling McAloon et al. (2000) Soybean milling process/ Biodiesel production Sheehan et al. (1998) Lignocellulosic biorefinery Laser and Lynd (2005) Burdens associated with E85 driving/ gasoline driving and B20 driving/ Kim and Dale (2006), Kim and Dale (2005b) Diesel driving US electricity production system Kim and Dale (2005c) Nitrogen fertilizer/ Phosphorus fertilizer Other data (e.g. fuels, potassium fertilizer, etc.) Office of Industrial Technologies (2000), Kim and Overcash (2000), International Fertilizer Industry Association (1998,2005), Pagani and Zardi (1994) TEAM TM (n.d.)

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 19 Table 2 Environmental performance of the corn grain based ethanol fuel system Unit Overall Biomass Vehicle Biorefinery production operation Crude oil g km -1-60.91 2.44-0.01-63.34 Nonrenewable energy MJ km -1-1.47 0.43 1.49-3.39 Greenhouse gas emissions g CO 2 eq. km -1-122.01 33.34 71.47-226.83 Acidification moles H + eq. km -1 0.0001 0.04-0.02-0.01 Eutrophication g N eq. km -1 0.11 0.25-0.10-0.04 Photochemical smog formation mg NOx eq. m -1 km -1-0.29 1.01-0.88-0.43

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 20 Table 3 Environmental performance of the corn stover based ethanol fuel system Unit Overall Biomass Vehicle Biorefinery production operation Crude oil g km -1-64.95 2.91-4.52-63.34 Nonrenewable energy MJ km -1-3.71 0.31-0.63-3.39 Greenhouse gas emissions g CO 2 eq. km -1-245.49 30.05-48.72-226.83 Acidification moles H + eq. km -1 0.10 0.01 0.10-0.01 Eutrophication g N eq. km -1 0.05-0.04 0.13-0.04 Photochemical smog formation mg NOx eq. m -1 km -1 3.34 0.31 3.46-0.43

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 21 Table 4 Environmental performance of the switchgrass based ethanol fuel system Unit Overall Biomass Vehicle Biorefinery production operation Crude oil g km -1-68.50 2.91-8.07-63.34 Nonrenewable energy MJ km -1-4.31 0.29-1.21-3.39 Greenhouse gas emissions g CO 2 eq. km -1-336.02-17.26-91.94-226.83 Acidification moles H + eq. km -1 0.10 0.04 0.07-0.01 Eutrophication g N eq. km -1 0.16 0.09 0.11-0.04 Photochemical smog formation mg NOx eq. m -1 km -1 3.38 1.05 2.75-0.43

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 22 Table 5 Environmental performance of the biodiesel fuel system Unit Overall Biomass Vehicle Biorefinery production operation Crude oil g km -1-118.28 10.65-7.72-121.21 Nonrenewable energy MJ km -1-8.71 0.76-3.59-5.89 Greenhouse gas emissions g CO 2 eq. km -1-588.04 16.09-197.40-406.73 Acidification moles H + eq. km -1 0.03 0.10-0.11 0.04 Eutrophication g N eq. km -1-0.15 0.58-0.74 0.02 Photochemical smog formation mg NOx eq. m -1 km -1-1.16 3.21-2.69-1.68

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 23 Table 6 Environmental performance of an integrated biorefinery Unit Corn grain based ethanol Integrated biorefinery A (grain plus stover) Integrated biorefinery B (grain plus switchgrass) Crude oil g km -1-60.91-63.54-66.58 Nonrenewable energy MJ km -1-1.47-3.46-3.98 Greenhouse gas emissions g CO 2 eq. km -1-122.01-231.00-309.22 Acidification moles H + eq. km -1 0.0001 0.09 0.08 Eutrophication g N eq. km -1 0.11 0.06 0.15 Photochemical smog formation mg NOx eq. m -1 km -1-0.29 3.66 3.67

Figure 1 System boundaries III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 24

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 25 Figure 2 Effect of ethanol yield on the ethanol derived from corn stover system [Current yield: 0.23 kg ethanol/kg of dry corn stover; Future yield: 0.34 kg ethanol/kg of dry corn stover; Energy: nonrenewable energy; GHG: greenhouse gas emissions; Acid.: acidification; Eutro.: eutrophication; Smog: photochemical smog formation]

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 26 Figure 3 Effect of ethanol yield on the ethanol derived from switchgrass system [Current yield: 0.22 kg ethanol/kg of dry corn stover; Future yield: 0.32 kg ethanol/kg of dry corn stover; Energy: nonrenewable energy; GHG: greenhouse gas emissions; Acid.: acidification; Eutro.: eutrophication; Smog: photochemical smog formation]

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 27 Figure 4 Traveling distance-oriented analyses for the relative environmental credits associated various biofuel systems. The environmental credit of the corn grain based ethanol system is the base case

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 28 Figure 5 Arable land-oriented analyses for the relative environmental credits associated various biofuel systems. The environmental credit of the corn grain based ethanol system is the basis case.

III.C. Biofuels_Life Cycle Analysis_S. Kim & B. Dale 29 Figure 6 Effects of changing the production capacity of lignocellulose based ethanol in the integrated biorefinery. Red lines represented integrated biorefinery A, and blue lines represented integrated biorefinery B. [Energy: nonrenewable energy; GHG: greenhouse gas emissions; Acid.: acidification; Eutro.: eutrophication; Smog: photochemical smog formation]