Evaluating fuel ethanol feedstocks from energy policy perspectives: A comparative energy assessment of corn and corn stover

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1 Energy Policy 35 (2007) Evaluating fuel ethanol feedstocks from energy policy perspectives: A comparative energy assessment of corn and corn stover Amanda Lavigne, Susan E. Powers Center for the Environment, Clarkson University, 8 Clarkson Avenue, Potsdam, NY , USA Received 20 October 2006; accepted 10 July 2007 Available online 30 August 2007 Abstract Concerns surrounding the continued, un-checked use of petroleum-based fuels in the transportation sector, the search for more sustainable, renewable alternatives, and the constraints of the existing supply infrastructure in the United States have placed a spotlight on biomass-derived fuels. The central question of the ethanol debate has changed from Should we make ethanol? to From what should we make ethanol? emphasizing the importance of understanding the differences between specific biomass supply systems for fuel ethanol. When presented with numerous options, the priorities of an individual decision maker will define which feedstock alternative is the most appropriate choice for development from their perspective. This paper demonstrates how energy data can be successfully used to quantify assessment metrics beyond a standard net energy value calculation, thus quantifying the relative value of ethanol supply systems. This value is defined based on decision-maker priorities that were adopted from national energy policy priorities: increased national energy security and increased conservation of energy resources. Nine energy assessment metrics that quantify detailed system energy data are calculated and a straightforward comparative assessment is performed between corn and corn stover feedstocks produced under the same farm scenario. Corn stover is shown to be more compatible with the national energy policy priorities and it is recommended that additional research be performed on utilizing this feedstock from the corn farm. r 2007 Elsevier Ltd. All rights reserved. Keywords: ethanol; Corn; Net energy value 1. Introduction The Energy Policy Act of 2005 (EPACT) reflects the recently galvanized drive to find alternative fuel sources and reinforces policy priorities that have been the focus of Congressional debate under the current administration: increased energy security, conservation of energy resources, and sustainable development of energy resources and supply systems (NEPD, 2001). The concerns surrounding the continued, un-checked use of petroleum-based fuels in the transportation sector, the search for more sustainable and renewable alternatives, and the constraints of the existing supply infrastructure in the United States have placed a spotlight on biomass-derived fuels. The EPACT calls for at least 7.5 million gallons of renewable fuels to be Corresponding author. Tel.: ; fax: address: lavignea@clakson.edu (A. Lavigne). blended into the national gasoline supply by the year 2012, and provides incentives for the production of these fuels from corn and other crops, plants, grasses, agricultural residues and waste products (Senate Committee on Energy and Natural Resources, 2005). During his 2007 State of the Union address, President Bush proposed to raise this goal to 35 billion gallons by 2017, approximately 6 times greater than the current national production. While research continues on various demand-side concerns surrounding the increased use of biofuels, such as vehicle energy efficiency standards and potential environmental impacts, these policies have shifted the central question of the ethanol debate from Should we make ethanol? to From what should we make ethanol? As the country moves forward with increasing ethanol production, it is critically important for government, industrial and agricultural decision makers to be able to understand the significance of implementing various supply-side combinations of /$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi: /j.enpol

2 A. Lavigne, S.E. Powers / Energy Policy 35 (2007) biomass feedstocks and conversion processes to enable informed decisions to be made. When presented with these feedstock/processing options, the priorities of an individual decision maker will define which alternative is the most appropriate choice for development from their perspective. For example, decision makers who prioritize reducing greenhouse gas emissions might select a very different supply system than those wishing to increase national energy independence. Recently, it has been argued that the traditional assessment focus on the net energy value (NEV) of ethanol supply systems does not provide adequate information about the nature of energy used. This very sensitive, aggregated and non-transparent metric does not contribute to an understanding of how different priorities would be met by the ethanol feedstock alternatives, thus suggesting the need for new assessment metrics (Hammerschlag, 2006; Farrell et al., 2006). This paper demonstrates how energy data can be successfully used to quantify numerous robust assessment metrics that illustrate the impacts of the energy use within alternative ethanol supply systems to meet the needs of decision makers who have different perspectives and priorities about our energy choices. The priorities considered here were adopted from national energy policy philosophies: increase national energy security and increase conservation of energy resources. The objective is to demonstrate how appropriate and transparent metrics allow confident assessment of different ethanol supply systems from different decision-maker perspectives by quantifying various critical aspects of the system energy utilization. Although these metrics are not independent, they do demonstrate the broader usefulness of more varied energy-related metrics that are less sensitive than a NEV calculation. The energy use priorities selected for this paper do not embody all of the significant issues involved with expanding the fuel ethanol industry within the national energy pool. However, they do address the baseline energy concerns related to increased ethanol production. Other concerns, including the availability and costs of feedstocks, environmental and human health impacts, and external costs and impacts, also need to be evaluated to ensure efficient and effective expansion of the ethanol industry. These aspects of the ethanol feedstock debate will be addressed in a separate paper. For the two energy-centric priorities focused on here, a set of assessment metrics are presented that illustrates the relative impacts of alternative ethanol supply systems from the perspective of a decision maker who embraces these national priorities. Ethanol supply systems utilizing corn as a feedstock versus corn stover feedstock are considered. The assessment metrics are quantified for both systems using data taken from current literature sources. The results of a straightforward comparative assessment using the quantified metrics are presented, followed by a discussion focusing on the central question: Which ethanol supply system allows these energy policy priorities to be realized? 2. Historically used energy metrics The historical debate surrounding the increased use of biomass ethanol within the transportation sector has been perpetuated by confusion regarding the NEV of ethanol supply systems. An NEV is typically calculated by subtracting the gross energy inputs to the system from the gross energy outputs. The NEV does not represent a complete energy balance but instead represents the net energy resources supplied and generated by human intervention in agricultural and engineered systems. Energy supplied by natural processes is not included. For example, the solar energy captured by biomass and the Earth s heat and pressure that contributed to fossil fuel generation are not included. Thus, a positive NEV represents a system that contributes to the overall supply of energy resources that can be readily utilized for human needs. Over the past few decades, the collective research on corn ethanol supply systems has provided a wide range of positive and negative NEV estimates (Fig. 1), fostering confusion and hindering increased incorporation of fuel ethanol into the transportation sector. This figure illustrates a general increase in NEV estimates over time due to agricultural advances such as increased corn yield per hectare and fewer chemicals required, and advances in the ethanol-processing facility including greater conversion efficiency and material input recycling. According to Shapouri et al. (2004), a majority of the differences apparent in Fig. 1 arise from the system boundaries, research assumptions, and specific data used by the researchers. For example, the three negative NEV estimates reported after 2000 are all associated with the work of one researcher, David Pimentel. Critics of Pimentel s work have pointed to his use of obsolete data concerning corn farm yields and fertilizer application rates, energy required for fertilizer production, and ethanolprocessing yields, as well as questionable assumptions regarding energy inputs for farm irrigation, labor, and machinery and ethanol-processing co-product credits as reasons for his continued low NEV estimates (Wang and Santini, 2000; Graboski, 2002). More recent comparative studies by Hammerschlag (2006) and Farrell et al. (2006) draw similar conclusions regarding Pimentel s work, as well as ethanol NEV studies in general. Both of these studies looked at prominent corn ethanol literature and the utility of data provided by the researchers. Hammerschlag (2006) recommends a shift away from the simple but debatable net energy metric to broader, more impact-based metrics. Farrell et al. (2006) suggest that, the net energy is an extremely sensitive metric that ignores critical differences in energy use data, and that finding replacements for this traditional energy metric would be a positive step. The NEV provides no information to decision makers regarding other critical energy issues such as percentage of fossil fuel inputs derived from imported petroleum, the use of renewable biomass as processing fuel, or the net transportation fuel produced by

3 5920 ARTICLE IN PRESS A. Lavigne, S.E. Powers / Energy Policy 35 (2007) NEV (MJ/L) Marland & Turhollow, 1990, 1991 Deluchi, 1991 OECD, 1994 TRW, 1980 Parisi, 1983 Ho, 1989 Lorenz & Morris,1995 Morris & Ahmed, Ag. Foods, 1999 Wang et al., 1999, 2001 Shapouri et al., 1995, 2002 Keeney & DeLuca, 1992 D. Pimentel 2001 Graboski, 2002 Shapouri et al., Kim & Dale, 2002 Farrel et al., 2006 Pimentel & Patzek, YEAR Fig. 1. Estimates of corn ethanol NEV over time. The general increase can be attributed to improvements on the farm and in the processing plant. (Agriculture and Agri-foods Canada, 1999; Ho, 1989; Keeny and DeLuca, 1992; Lorenz and Morris, 1995; Marland and Turhollow, 1991; Morris and Ahmed, 1992; Organisation for economic Co-operation and Development (OECD)/International Energy Agency, 1994; Parisi, 1983; Pimentel, 1991, 2003; Pimentel and Patzek, 2005). the system. Additionally, this metric does not capture other broader environmental concerns such as changes in land use, effects on the carbon cycle, and geographic redistribution of emission impacts due to decentralization of fuel production. Thus, the recommendations to move away from the reliance on NEV to make policy decisions regarding increased ethanol production should be heeded. Hammerschlag (2006) and Farrell et al. (2006) also include recent cellulosic biomass studies in their reviews and mention the potential advantages cellulosic ethanol may have over traditional corn ethanol. Cellulosic feedstocks are gaining favor in part because the utilization of corn ethanol as a transitional fuel source has drawn criticism from several fronts for reasons that include the use of food resources for fuel, increased land use diverted to farming, and increased environmental impacts from fertilizers and pesticides (Pimentel, 2001; von Blottnitz and Curran, 2006). Additionally, biomass wastes produced by the forestry, agriculture, consumable ethanol and foodprocessing industries have recently drawn considerable interest as fuel ethanol feedstocks. Corn stover, an agricultural residue left in the field after corn is harvested, has become the focus of numerous ethanol feedstock studies (Aden, et al., 2002; Perlack and Turhollow, 2003; Atchison and Hettenhaus, 2003; Sheehan et al., 2004). Based on recent recommendations in the literature (Hammerschlag, 2006; Farrell et al., 2006) and the widely varying NEV estimates (Fig. 1), it is clear that future analyses of alternative fuel supply systems must strive to overcome historical tendencies to aggregate energy data to focus on the NEV. The calculation of one highly sensitive and variable number meant to represent the entire fuel supply system fails to provide the information decision makers need to promote efficient and effective expansion of the ethanol industry more broadly into the national transportation energy pool. While the NEV can be a useful metric, more relevant and robust assessment metrics, using transparent and detailed data, are required to provide a broader range of critical information to decision makers. 3. Assessment metrics for national energy priorities Considering underlying energy policy priorities that place importance on increased energy security and resource conservation, assessment metrics related to the specific energy consumed within the ethanol supply system are required. Energy security has evolved into two key goals: increased domestic energy supply and decreased dependence on foreign imports (Energy Efficiency and Renewable Energy Office, 2006). While the United States is self-sufficient in virtually all other energy resources, approximately 60% of our Nation s oil and 20% of our natural gas net requirements are imported (Annual Energy Review, 2006). In early 2007, approximately 70% of the US daily consumption of over 21 million barrels of oil was for transportation fuels (Energy Information Administration, 2007). Considering these statistics, an ethanol supply system that increases domestic energy supply and/or reduces consumption of foreign oil and natural gas imports would be compatible with the energy security priority and would be a favorable system for a decision maker who holds energy security in high regard. To illustrate whether a supply system embodies this priority, the NEV can actually be a useful baseline metric, demonstrating the contribution of energy resources to the domestic supply. Yet, to determine the reliance of a specific supply system on imported energy, greater detail and transparency is required to quantify how much of the energy resources consumed are oil or natural gas. Rather than aggregating energy data as is done with the NEV,

4 A. Lavigne, S.E. Powers / Energy Policy 35 (2007) Table 1 Assessment metrics chosen to quantify energy values to support the perspective of a decision maker who subscribes to the identified energy policy priorities Policy priority Desired knowledge (per liter of ethanol produced) Metric Units General energy metrics Total fossil energy resources consumed Fossil fuel inputs MJ/L Total petroleum energy resources consumed Oil-derived inputs MJ/L Total renewable energy resources consumed a Renewable inputs MJ/L Renewable inputs ¼ Energy resource inputs from biomass+12% electricity b Increased energy security Net energy resources produced Net energy value (NEV) MJ/L NEV ¼ (Total energy outputs) c (Total energy resource inputs) a Percentage of energy consumed from foreign resources % foreign % % foreign ¼ % oil inputs þ20% natural gas inputs Total inputs Percentage of energy consumed from domestic resources % Domestic ¼ 100 % Foreign % domestic % Energy resource conservation Percentage of energy resources consumed that are renewable % renewable % Renewable inputs % renewable ¼ 100 Total energy resource inputs Energy efficiency of the supply system Energy efficiency ratio MJ/MJ Energy efficiency ¼ Total energy resource outputs Total energy resource inputs Net energy resources for transportation end use Net transportation fuel MJ/L Net transportation fuel ¼ Total transportation fuel outputs Total transportation fuel inputs a Does not include solar energy inputs to grow biomass or embodied energy of biomass as an input to processing. b Based on US standard electricity generation mix, as defined by GREET. c Includes co-product credits. energy input data that identifies the specific resources (i.e. oil, coal, diesel and natural gas) utilized over the life cycle need to be quantified and communicated separately. In this way, the consumption of imported resources can be quantified and compared independently from domestically produced resources. Generally, the conservation of energy resources implies a reduced use of all energy resources within the ethanol life cycle. Therefore, a more efficient system, utilizing fewer energy resources to produce a unit of fuel output, would be compatible with the energy resource conservation priority. More specifically, conservation of energy resources implies a reduction in the use of non-renewable energy resources per volume of fuel output. This perspective can be applied to all fossil fuel inputs to the system, or narrowed to the consideration of liquid transportation fossil fuels, due to the fact that a liquid transportation fuel is the desired product of the system. Consider that the historic NEV argument implies: if it takes more energy resources to produce a gallon of fuel than you can get out of that gallon of fuel, it is not worth producing it. Yet, from a transportation viewpoint, ethanol may have an intrinsically higher value than other forms of energy because it is a liquid fuel that can be readily utilized in an automobile, requiring only minor adaptation to our current infrastructure. Most of the energy used to create ethanol is generally inaccessible for the purposes of operating an automobile. After the ethanol conversion process, however, that energy is accessible in the form of a liquid fuel that can be directly mixed with gasoline. Thus, if the desired end is transportation fuel, it might be more important to look at how much transportation fuel was utilized per volume of transportation fuel output as opposed to other fossil fuels that cannot be directly used in a vehicle. Again, a difference in the decision-makers priorities and perspectives will affect which data will be critical to the decision. Therefore, both of these resource conservation perspectives are addressed: conservation of all fossil fuels, and conservation of liquid transportation fuels. Based on these energy policy priority considerations, nine assessment metrics have been established for the assessment of the two-feedstock scenarios (Table 1). This set of metrics has not been defined under the strict tenants of multi-criteria decision-making theory (Hobbs and Meier, 2000), and are not meant to be mutually independent from one another. Rather, each metric was established to highlight a different aspect of the same data set so that the specific energy use profiles of each system can be more clearly understood. Additional priorities, such as reducing atmospheric emissions or human health impacts, which are also important to consider for ethanol supply systems, will be addressed in a later paper. 4. Assumptions and data sources Wang and colleagues developed and used the Greenhouse Gases, Related Emissions and Energy Use in Transport model (GREET) to provide numerous analyses

5 5922 ARTICLE IN PRESS A. Lavigne, S.E. Powers / Energy Policy 35 (2007) of fuel ethanol supply systems utilizing corn and dedicated cellulosic crops as ethanol feedstocks (Wang et al., 1997, 1999; He and Wang, 2000; Shapouri et al., 2002). Wang et al. (1999) provide a direct comparison between traditional gasoline and ethanol made from different feedstocks, providing an example of a comparative analysis among feedstocks and different production scenarios. The GREET model is relatively transparent, facilitating access to the basic data necessary to quantify the metrics proposed in this paper. The development and evolution of GREET is documented in five major reports published by the Department of Energy (Wang, 1996, 1999a, b, 2000, 2001). For any given transportation fuel/technology combination, GREET calculates energy use and emissions over the lifecycle of fuel production and use. Direct energy inputs for each stage are represented, and total energy use including direct and upstream inputs from all sources is calculated. The fossil fuel and petroleum use fractions of this total are specifically quantified. GREET addresses the three major stages of a fuel life cycle from feedstock production to fuel production and vehicle operation, as well as specific activities within each stage. EPA databases provide the foundation for the parametric assumptions required for GREET to perform the calculations for each fuel cycle, although more detailed input data source assumptions are well documented (Wang, 1999a, b). This model provides detailed data relating the direct energy inputs for the ethanol system to upstream energy use and atmospheric emissions. This level of detail is critical for quantifying the assessment metrics proposed for this work. Because some of these details become aggregated within the GREET output, additional work was required to adapt the model to separate these data to quantify the specific metrics defined here. Assumptions regarding lifecycle energy use for corn stover as an ethanol feedstock were documented by Sheehan et al. (2004). Their LCA gathered information regarding energy, environmental, and economic aspects of a corn stover feedstock scenario. The model developed by this team was designed to be a framework for discussing the benefits and trade-offs of substituting gasoline with ethanol made from corn stover (Sheehan et al., 2004). The system boundaries encompassed the production and collection of stover on the farm, the transport of stover to the processing facility, distribution of ethanol to retailers, and the use of ethanol as E85. A similar system boundary was set for the production and use of gasoline for comparison. This study provided an example of a detailed analysis and assessment for one ethanol feedstock option, and incorporated many metrics that could be used to determine the value of this feedstock from the energy policy perspectives defined here. While Sheehan et al. (2004) do offer some qualitative comparisons between stover and other feedstocks related to the energy security issue, the data for the other feedstocks were derived using a different methodology and set of assessment tools, which introduces uncertainty into their comparison. Thus, while considerable analysis has been completed regarding corn, and interest in stover is rising, these two feedstocks have not been assessed as feedstocks generated under the same farm scenario, nor have they been directly compared with regards to life cycle energy use. Notably, when these two feedstocks are considered under separate analyses, the energy associated with the biomass itself is treated differently. Typically, for corn, the energy content of the biomass is not considered as an energy resource input to the life cycle energy inventory (Wang et al., 1999; Shapouri et al., 2002). This can easily be explained, considering that the output of one life cycle phase (i.e. corn out of the farm) cancels out the input to another (i.e. corn into the processing plant). Yet, when cellulosic feedstocks, such as corn stover, are considered, the intrinsic energy of the feedstock is often considered as an input to the processing plant (Sheehan et al., 2004). This marked difference may be due to the fact that the lignin, a waste material from the cellulosic ethanol conversion process, is often designated for feed into a boiler/generator where it would be burned to produce the thermal energy and electricity for the plant (Sheehan et al., 2004). This difference in how the energy value of the biomass is considered can have a significant impact on the overall energy analysis associated with each system. A look at corn and stover under similar assumptions regarding biomass energy content is warranted. Additionally, the need to consider the perspectives of decision makers has been mentioned by recent researchers as a priority (Farrell et al., 2006), but is generally not directly addressed within analyses of ethanol supply systems. An analysis that directly compares corn and stover and provides detailed energy data that quantify which specific energy types and resources are being utilized during each stage of the life cycle allows a decision maker with energy security or energy resource conservation priorities the ability to decide which of these feedstock options would be the most appropriate for development from their particular perspective. 5. Assessment boundaries and functional unit Corn and corn stover feedstocks generated under the same farm scenario have been utilized for this analysis. Since this assessment focuses on trade-offs in the processing of one fuel type, as opposed to trade-offs between fuel types, all data are calculated based on the production of 1 L of ethanol. Thus, the life cycle steps include only feedstock production and the ethanol-processing phases. Energy requirements for the transportation of the feedstock from its production location to the processing plant are also included. The use of ethanol as a fuel is not included in the assessment because it is assumed that the liter of ethanol, whether manufactured from corn or stover, will be used in the same manner, identical for each feedstock option.

6 A. Lavigne, S.E. Powers / Energy Policy 35 (2007) Energy used for each life cycle stage includes both the energy used directly in that stage and energy used in processes that are upstream from that life cycle stage. Direct energy refers to the actual use of a fuel, such as the diesel fuel used by farm equipment. Upstream energy is defined as the energy required to manufacture or produce chemical or energy inputs to the two primary life cycle stages. For example, significant energy is consumed to manufacture nitrogen fertilizer that is a required input for corn and stover growth. In contrast, upstream energy requirements for chemical production for ethanol processing are not included due to the negligible energy consumption associated with the chemical inputs (Wang, 1999a, b, 2001). 6. Analysis methodology The GREET model was chosen as a foundation for the corn farm and ethanol production scenarios due to the transparency of the Excel spreadsheet interface, as well as the confidence in the model results other researchers have reported (Shapouri et al., 2002; Farrell et al., 2006; von Blottnitz and Curran, 2006). This analysis uses version 1.5a of the GREET model as a baseline. Although newer versions of the model (1.6 in April, 2005, and 1.7 in September, 2006) are now available, a thorough examination of version 1.5a was undertaken during the initial stages of the analysis and all assumptions, default data values, and calculations were documented. Updated assumptions and default values incorporated into version 1.6 were assessed (Wang, 2001) and alterations to the working copy of version 1.5a were made where appropriate. Specifically, the ratio of dry and wet mills for corn ethanol processing was increased to a 50% split, and the direct energy requirements for each processing scenario were increased to 11.1 MJ/L (40,000 Btu/Gal) to more closely match the updated default values. Based on other literature sources (Shapouri et al., 2002, Graboski, 2002) diesel fuel (1%) and electricity (9%) process fuel input share percentages were also added. The data reported by Sheehan et al. (2004) were used for the corn stover feedstock production scenario. These values were converted into the units embedded in the GREET corn farm scenario, and plugged into the appropriate input data cells to calculate corn farm energy use related to the harvest of stover for feedstock purposes. Because corn is considered to be the primary product of the farm, and due to the fact that the stover cannot be harvested without harvesting the corn, no other farm-related energy was attributed to the stover. The energy resource use attributed to the stover includes additional machinery fuel for harvesting and additional chemical application to compensate for the removal of nutrients from the field when the stover is not returned to the soil. A combination of converted data taken from Sheehan et al. (2004) and default data values associated with the herbaceous biomass ethanol production scenario embedded in the GREET model (Wang et al., 1999) were used to represent the corn stover ethanol production scenario. This scenario includes the co-generation of electricity and steam through the burning of lignin and syrup waste outputs from the production process. The data readily expressed by the GREET model summarizing direct and total energy use within each ethanol life cycle phase were documented for each feedstock option, including the fossil and petroleum fractions of the total energy input values. All values have been converted to represent the inputs and outputs for the production of 1 L of anhydrous ethanol, with a lower heating value of 21.1 MJ/L (76,000 BTU/gal). For the upstream energy consumed, GREET output lumps all energy sources together. This data aggregation prevents the accurate quantification of the defined energy metrics. Thus, the underlying model equations were manipulated to provide the appropriate fundamental upstream energy use data. By dismantling each energy use equation associated with total energy inputs to the system, a breakout between direct and upstream energy could be determined for each energy source type. 7. Consideration of co-products In this assessment, co-products are considered to be marketable commodities other than ethanol that are produced within the processing stage but are not utilized within the system boundaries. Because ethanol is the primary product, no allocation of input process energy is undertaken between the ethanol and the co-products, but energy credits are assigned to more accurately represent the outputs of the system for net energy calculations. For corn processing, the default co-product energy credit values from GREET 1.5a are utilized. The model uses an alternative product-replacement value-accounting system to assign these energy credits. GREET considers dried distillers grains and solids (DDGS) generated in the dry mill process to be a suitable replacement for corn and soybean meal, and co-products from the wet-mill process to replace corn, soybean meal, nitrogen in urea, and soybean oil. The attributed credits are based on the avoided energy resource use due to manufacturing or processing that would occur by replacing these products with the ethanol co-products within the market. For stover processing, the only true co-product considered is the electricity produced through co-generation that is not utilized within the processing facility and is exported to the grid. In a similar manner to the displacement value method used to assign corn ethanol co-product credits, the actual electricity output is credited along with the equivalent upstream energy required to produce an equal amount of electricity within the US standard grid. 8. Results and discussion 8.1. Direct energy flows Figs. 2 and 3 represent the direct energy flows calculated for the corn and stover ethanol supply systems, respectively.

7 5924 ARTICLE IN PRESS A. Lavigne, S.E. Powers / Energy Policy 35 (2007) Although electricity and chemical inputs truly represent upstream energy resource use, the values provided for these energy carriers illustrate the actual utilization, in energy equivalents, in the farming and processing stages. Fig. 2 includes the default data from the GREET model, manipulated to represent the energy flows for the production of 1 L of ethanol, as well as the additional distribution of processing input sources (fuel and electricity values) adapted from literature. Fig. 3 represents the direct energy flow data for the stover ethanol system taken from Sheehan et al. (2004), adapted to fit the GREET input data requirements for the corn farm, and the herbaceous biomass-processing scenario. Both of these figures show the cycling of biomass energy within the ethanol system boundaries (dashed line). This cycling allows the inherent energy value of the feedstock to cancel out, since the output of one stage (the farm) equals the input for another (the processing plant). In calculating the standard NEV metric, this cancellation seems to be generally assumed for other corn ethanol energy analyses (the corn energy is never mentioned as a farm output or processing input) (Wang et al., 1999; Shapouri et al., 1995, Corn 4.3E+01 MJ/L Corn Farming 2.1E+00 MJ/L 2.5E-02 MJ/L 2.6E+00 MJ/L 2.2E-01 MJ/L Electricity Fertilizer Pesticide Transportation 5.3E-01 MJ/L Corn Electricity 4.3E+01 MJ/L 1.0E+01 MJ/L 9.7E-01 MJ/L Ethanol Processing 2.1E+01 MJ/L 5.4E+00 MJ/L Ethanol Co-Products *DDGS *Corn Oil *Gluten Meal Fig. 2. Direct energy flows per liter of ethanol produced using corn feedstock. 6.4E-01 MJ/L Stover 5.3E+01 MJ/L Corn Farming (Stover Harvest Only) 0.0E+00 MJ/L 1.4E+00 MJ/L. 0.0E+00 MJ/L Electricity Fertilizer Pesticide Transportation 4.8E-01 MJ/L Stover Electricity Thermal Thermal Electricity 5.3E+01 MJ/L 2.8E-01 MJ/L 1.7E+00 MJ/L 1.0E+01 MJ/L 1.0E+01 MJ/L 1.7E+00 MJ/L Ethanol Processing B/B T.G. 2.1E+01 MJ/L 3.0E+01 MJ/L. 3.0E+01 MJ/L Ethanol Waste *Lignin *Syrup Electricity 2.6E+00 MJ/L Fig. 3. Direct energy flows per liter of ethanol produced using stover feedstock (B/B ¼ boiler/burner unit; T.G. ¼ turbo generator unit).

8 A. Lavigne, S.E. Powers / Energy Policy 35 (2007) ; Graboski, 2002), but not always considered within cellulosic ethanol energy analyses, when feedstocks such as corn stover are considered (Sheehan et al., 2004; Wang et al., 1999). This difference is generally attributed to the consideration of thermal and electric co-generation using lignin and syrup waste products within cellulosic ethanol plants. Yet, the inclusion of the total biomass energy as a processing input for cellulosic feedstocks does not allow for a direct comparative assessment with other feedstocks, such as corn. In keeping with the philosophy of most corn ethanol studies and recognizing that the stover is not otherwise used as an energy resource, the analysis presented here does not count the biomass energy input against the ethanol output and the co-product credits for either feedstock. This produces standard results for the corn scenario, but changes the quantifiable metrics for stover. If we consider the co-generation (co-gen) facility as a separate stage within the stover ethanol life cycle in a manner equivalent to farming and processing, then the cycling of biomass energy for both scenarios can be comparably represented. Fig. 3 shows the stover energy value cancelling as an output from the farm and an input to the processing. The thermal and electric processing input requirements and the energy value of the waste lignin and syrup outputs are also represented. The lignin and syrup energy values are included in the NEV calculation only if co-generation is considered, whereby these wastes become energy resources and are considered an output from the processing facility and an input to the co-gen facility. Similar to the biomass energy, these output/input values cancel out of the NEV calculation. Also, the co-gen facility produces thermal and electric output, which can be cycled into the processing facility, allowing for another output/input cancellation. The cycling in this scenario results in the consideration of the fuel input to the processing facility as the only input for this stage to be counted against the system energy output when calculating the NEV for the stover system. The true co-product in this scenario is the extra electricity produced, which is in excess of that required by the processing facility and is represented by the flow that does not cycle back into the system boundary. This electricity can be counted as co-product energy credit against the system energy input within the NEV calculation. This coproduct credit and the biomass energy cycling assumptions represented in Fig. 3 are utilized to calculate the NEV for the stover feedstock scenario in Section 8.2. For true waste feedstocks, this biomass cycling/cancellation may not be as obvious, as the sub-system that produced the feedstock originally might not be included in the system boundary at all. In these cases, in order to make fair comparisons, the biomass energy input could be considered on the same level as solar energy inputs to the farm free energy. It has energy value, but would otherwise not be considered an energy resource. Although there will be costs associated with transportation, and perhaps acquisition, the energy in the biomass itself would otherwise have been wasted, and therefore, from an NEV perspective, should not be counted as an input to the system Quantifying total energy inputs by source Fig. 4 demonstrates the level of detail related to the source of direct and upstream energy use that can be 7.3 MJ/L Total Input Residual Oil (1%) Natural Gas Coal (76%) (1%) LPG (2%) Gasoline (4%) Production Diesel (16%) 0.7 MJL Upstream Input = 3.3 MJ/L (45%) Direct Input = 4.0 MJ/L (55%). Electricity Production 0.4M J/L 2.2 MJ/L Pesticide (3%) K 2 O (1%) P 2 O 5 (2%) N (94%) (43%) Energy Mass N (74%) (54%) P 2 O 5 (11%) (25%) K 2 O (6%) (20%) Pest. (9%) (1%) 0.4 MJL 3.6 MJ/L Nitrogen Fertilizer RO (1%) D (1%) Elec. (25%) NG (73%) Chemical Production Corn Farm LPG (13%) G (17%) NG (21%) D (49%) Ethanol Processing D (1%) NG (34%) C (65%) (3%) (54%) Fig. 4. Life cycle natural gas inputs to produce 1 L of corn ethanol (N ¼ nitrogen, RO ¼ residual oil, D ¼ diesel, NG ¼ natural gas, LPG ¼ liquefied petroleum gas, G ¼ gasoline, C ¼ coal).

9 5926 ARTICLE IN PRESS A. Lavigne, S.E. Powers / Energy Policy 35 (2007) obtained when the aggregated upstream energy data provided by GREET are broken down. As an example, this figure specifically tracks natural gas (NG) for both direct and upstream uses in the production of 1 L of corn ethanol. The total upstream NG use (3.3 MJ), which represents 45% of the total life cycle NG use (7.3 MJ), has been teased out of the aggregated GREET data and allocated as inputs required for fuel production, electricity production, and farm chemical production. The input for fuel production (0.7 MJ) shows how much natural gas is used in the production of all fuels required over the corn ethanol life cycle. The split of this among fuel types is represented by the accompanying pie chart. For example, 16% of the 0.7 MJ of NG was used in the manufacture of all the diesel fuel used directly on the farm, for transportation, and in the processing facility. The 0.4 MJ required for electricity production is based on the US standard generation mix provided by GREET, where NG represents approximately 15% of total electricity feedstock. The utilization of the electricity produced using NG has been attributed to each life cycle phase according to the percentages provided with the dashed line representing electricity distribution from the generating facility. Very little electricity generated using NG is required on the farm (3%) compared with the requirements for chemical production and ethanol processing. A majority of the upstream NG use is for farm chemical production (2.2 MJ), with most of the input required for nitrogen (N) fertilizer production (94%, or 2.1 MJ). The percentage breakdown of total energy inputs for N fertilizer production is included, showing that NG contributes 73% of the total energy input requirements. The fact that N fertilizer is the most heavily used on the farm (54% of chemical input by mass), coupled with the high NG requirement for its production, results in the relatively large upstream NG input for farm chemical production. The direct NG inputs (3.6 MJ) are divided between the farm and the processing facility. Ninety percent of the Corn Residual Oil Stover MJ/L Upstream Upstream for Chemicals Upstream for Electricity Upstream for s Biomass Coal 4 Direct 4 LPG N Gas Gasoline Diesel 2 2 Upstream 0 Farm Trans Process 0 Farm Trans Process Renewable MJ/L Petroleum Direct Other Fossil s Farm Trans Process Farm Trans Process Fig. 5. Energy inputs by source and life cycle phase. Graphs (A) and (C) represent the energy input data for corn feedstock and (B) and (D) are for stover. The upper graphs illustrate energy input data by fuel and life cycle stage. The pie graph within (A) represents the individual fuel components of upstream energy requirements for farm chemical production.

10 A. Lavigne, S.E. Powers / Energy Policy 35 (2007) directly used NG occurs at the ethanol-processing facility. This comprises 34% of the total energy requirements within the plant. The detailed breakdown of direct and upstream energy use by source and lifecycle stage illustrated in Fig. 4 for NG was required for all fuels to calculate the energy metrics defined in this paper. The resulting data are summarized in Fig. 5 for corn and stover ethanol supply systems. Both upstream and direct energy use are represented for each life cycle stage. The top set of graphs represents all of the system energy inputs for corn (A) and stover (B) broken down by each individual source type. The upstream energy requirements for chemical, fuel, and electricity production have been separately identified. The farm chemical production inputs are more clearly illustrated using the pie graph in (A). This level of detail was obtained for all upstream categories. From this graph, it is clear that a majority of the upstream inputs for farm chemical production are NG, reinforcing the breakout percentages from Fig. 4. The bottom set of graphs aggregates these sources according to the general energy types important for the energy metrics defined here. The renewable energy inputs attributed to corn are derived from a percentage of the electricity inputs (12%), based on the US standard electricity generation mix provided by GREET. The slight difference in total energy consumed between the top graphs and the bottom graphs represents the fraction of electricity generation inputs derived from nuclear power. These inputs are included in graphs (A) and (B), but excluded from graphs (C) and (D). In Fig. 5, the total energy inputs, including those derived from internal cycling of biomass energy within the system boundaries are shown to more clearly illustrate the energy requirements for ethanol processing. Although this internal cycling of energy flows results in a zero net energy use and was critical for calculating comparable NEVs, these flows still need to be integrated into metrics defining the actual energy resources consumed in each stage. From this figure, numerous conclusions can be drawn about each ethanol supply system: Overall, the processing stages for both feedstocks are the most energy intensive, and use nearly equivalent amounts of energy (12.5 MJ/L for corn; 11.5 MJ/L for stover). The stover system utilizes far fewer non-renewable inputs per liter of ethanol produced (2.6 vs MJ/L for corn), primarily due to the energy recovered from lignin waste by the co-generation facility. The upstream energy inputs necessary to produce electricity significantly contribute to the total energy use within the corn system, adding 3.0 MJ/L. The smaller chemical application required on the farm in the stover ethanol system (1.3 vs. 3.8 MJ/L for corn) substantially lowers the total energy used. The corn system uses more petroleum inputs (3.1 vs. 1.5 MJ/L for stover) thereby creating a greater transportation fuel deficit that needs to be replaced with the ethanol product Quantification of assessment metrics The level of detail in the analysis of energy data that is illustrated in Fig. 4 and summarized in Fig. 5 allows the energy assessment metrics defined in Table 1 to be quantified for both supply systems. These values are presented in Table 2. The calculated NEVs for both systems are positive, although the NEV for the stover system is approximately 3.9 times greater than the NEV of the corn system, due primarily to the co-generation of thermal and electrical energy inputs for stover ethanol processing. With this cogeneration, the only energy input to the processing facility is the diesel fuel used to operate on-site heavy machinery (0.3 MJ/L). Additionally, the extra electricity produced (2.6 MJ/L) contributes a co-product credit based on the displaced energy that would be required to produce this amount of electricity with the standard US mix and production efficiency. Calculating the direct energy used for this equivalent electricity generation (4.3 MJ/L) and the upstream energy that would be attributed to this fuel production (0.2 MJ/L), the total credit assessed for the exported electricity is 4.5 MJ/L. Considering the other inputs to the farm and transportation stages (2.1 and 0.3 MJ/L, respectively), the stover system produces an NEV of 22.9 MJ/L, which is actually greater than the LHV of the ethanol itself (21.1 MJ/L). But the sensitivity of this NEV estimate needs to be examined. The consideration of co-product credit has been the subject of debate within many ethanol system analyses. How co-products are treated and credited is one of the primary contributing factors to the sensitivity and uncertainty of NEV estimates (Shapouri et al., 1995, 2002; Wang et al., 1999a; Kim and Dale, 2002). Table 2 Quantified energy assessment metrics Metric Corn Stover Units Energy use (w/cogen) Fossil fuel inputs MJ/L Petroleum inputs MJ/L Renewable inputs MJ/L Energy security Net energy value MJ/L % foreign inputs % % domestic inputs % Resource conservation % renewable inputs % Energy efficiency MJ/MJ Net transportation energy MJ/L

11 5928 ARTICLE IN PRESS A. Lavigne, S.E. Powers / Energy Policy 35 (2007) The assumption of co-generation within the stover system has an enormous impact on the definition of system co-products. Co-generation allows the energy embodied in the stover processing wastes to be recognized and counted as an energy output that in turn cancels the required heat and power input for this stage. If cogeneration was not considered within the system boundaries, then the lignin and syrup could be considered true waste products of the processing facility with no energy value attributed to them. The heat and power energy requirements for processing would then become external energy inputs, and the NEV would drop to 6.7 MJ/L for the stover system, placing it virtually equal to the NEV for the corn system. Yet, it could be argued that even without co-generation within the stover ethanol system, the lignin and syrup still have the potential to be used for this purpose and therefore could be considered co-products that warrant an energy credit assignment. Under the displacement value method employed for the other co-products in this assessment, the inherent energy value of the lignin and syrup would not be considered but the energy value of the products they could displace would be. This method would compare the energy required to produce an amount of heat and power through conventional pathways (i.e. the standard US fuel mix and generation efficiency for electricity production) equivalent to the amount that could be derived from the lignin and syrup under probable generation conditions. For example, if the efficiency of the boiler/burner turbo generator used in this assessment is considered standard for the combustion of lignin and syrup, then a total of 4.3 MJ/L of electricity can be produced. In order to produce this much electricity using the standard US generation mix and efficiency factors, 7.8 MJ/L of energy are required. Therefore, this amount of credit for potential electricity production would be assessed to the lignin and syrup co-products. A similar calculation can be made for thermal energy production based on the use of natural gas to produce heat and steam within the production plant. In this case, the lignin and syrup would displace a total of 10.3 MJ/L of fossil energy. Using the displacement method for co-product credit assessment in this case would make the NEV estimate for the system 24.2 MJ/L. The additional 2.5 MJ/L of net energy under this scenario is due to the upstream processing energy that would be required for the production of the displaced fuel and electricity. The drastic changes in a calculated NEV for stover due to differing assumptions and treatment of co-product credits highlight the sensitivity of NEV as an assessment metric and emphasize that caution must be taken when using this number as the only metric when comparing alternatives. Although the other metrics presented here are also sensitive to the co-generation assumption, the tendency to aggregate all energy data into a single NEV metric can mask energy use profiles that are critical to other perspectives. Thus, even if an NEV is rigorously calculated, it still does not provide enough information to understand the impact of an ethanol supply system from the energy policy priorities considered. For these reasons, the additional assessment metrics presented in Table 2 were chosen to help illustrate the aspects of system energy use critical to these priorities. Considering the energy security perspective, the corn system consumes approximately twice the oil-derived energy use of the stover system. Corn ethanol also utilizes 7 times more total fossil fuel energy inputs, and requires over twice the percentage of foreign-derived fossil fuels than stover ethanol. Eighty percent of the inputs to the stover system are renewable, based on the assumption that the lignin and syrup wastes from the fermentation process are burned for co-generation. Based on these metrics, the stover ethanol supply system has a definite advantage over the corn ethanol supply system from an energy security perspective. The resource conservation metrics enable a similar conclusion to be drawn. The stover system shows much higher numbers than the corn system in both the percentage of renewable energy inputs, and the energy efficiency of the system as a whole. The net transportation energy metric, which reflects the production of energy that is directly usable in our current transportation system, is the only metric where the two systems are relatively close to each other as compared with the transportation fuel energy value of ethanol (21.1 MJ/L of ethanol), very little transportation energy is consumed in either system (3.1 MJ/L for corn and 1.5 MJ/L for stover), although the value for corn is almost twice the value for stover Implications Reviewing the quantified assessment metrics, it is obvious that corn stover is a more favorable ethanol feedstock than corn grain from the perspectives of energy security and resource conservation. The potential for the cogeneration of thermal energy and electricity within the stover ethanol system places this feedstock in a more complimentary position than corn with respect to the national energy policy perspectives considered in this study. However, the advantages are still apparent even if cogeneration is not utilized within the processing plant. The difference in the energy required to manufacture N fertilizer for corn has a marked impact on the metrics related to both priorities. Chemical manufacture is extremely energy intensive, relying heavily on fossil fuels, a majority of which falls within the foreign import category. Marketing the corn grown on the farm for other uses, then returning to the field to harvest the stover for fuel ethanol production seems to be a logical approach from the perspective of one who is concerned with increasing energy security and conserving energy resources. The utilization of stover as an ethanol feedstock could help alleviate some of the economic hardship faced by American corn farmers in recent years. The assessment metrics developed for this analysis clearly quantify the superiority