Conference Paper

NREL/CP-6A2-45805

July 2009

Life Cycle Assessment of the 

Energy Independence and 

Security Act of 2007: Ethanol – 

Global Warming Potential and 

Environmental Emissions 

Garvin A. Heath, David D. Hsu, Daniel Inman,

Andy Aden, and Margaret K. Mann

Presented at the American Society of Mechanical Engineers 

(ASME) Third International Conference on Energy Sustainability

San Francisco, California

July 19-23, 2009
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LIFE CYCLE ASSESSMENT OF THE ENERGY INDEPENDENCE AND SECURITY ACT OF 2007: 

ETHANOL – GLOBAL WARMING POTENTIAL AND ENVIRONMENTAL EMISSIONS

Garvin A. Heath

Strategic Energy Analysis Center, National Renewable Energy Laboratory

Golden, Colorado, USA

David D. Hsu 

Strategic Energy Analysis Center, National Renewable Energy Laboratory

Golden, Colorado, USA

Daniel Inman

National Bioenergy Center, National Renewable Energy Laboratory

Golden, Colorado, USA

Andy Aden

National Bioenergy, National Renewable Energy Laboratory

Golden, Colorado, USA

Margaret K. Mann

Strategic Energy Analysis Center, National Renewable Energy Laboratory

Golden, Colorado, USA

INTRODUCTION

Strategies to reduce the dependence of the United States on 

foreign oil, increase the use of renewable energy, and lessen the 

contribution to global warming have received significant 

attention. National adoption of such strategies could significantly 

impact America’s economy and security as well as global climate 

change. The Energy Independence and Security Act of 2007 

(EISA) mandates specific renewable energy market penetration 

targets for the year 2022 [1]. For liquid transportation fuels, the 

2022 EISA mandate is 36 billion gallons per year (bgy) of biofuel, 

of which 21 bgy must come from feedstocks other than corn 

starch. Despite this legal mandate for renewable biofuels, many 

questions remain unanswered with regard to the potential 

environmental effects of such a large increase in the production 

and use of biofuels. In addition to specifying volumetric 

standards for these renewable fuels, EISA establishes 

greenhouse gas mitigation standards. The objective of this study 

is to use life cycle assessment (LCA) to evaluate the global 

warming potential (GWP), water use, and net energy value 

(NEV) associated with the EISA-mandated 16 bgy cellulosic 

biofuels target, which is assumed in this study to be met by 

cellulosic-based ethanol, and the EISA-mandated 15 bgy 

conventional corn ethanol target. Specifically, this study 

compares, on a per-kilometer-driven basis, the GWP, water use, 

and NEV for the year 2022 for several biomass feedstocks. 

METHODS

Life cycle assessment is the method used to determine the 

global warming potential of the production and use of the fuel.

LCA is a way of looking at a process from “cradle to grave.” In 

other words, LCA tracks the net emissions and non-renewable 

energy and non-renewable materials that go into not only the 

main process of interest, but also processes that go into 

intermediate feedstocks associated with that process. Life cycle 

assessment methodology has been codified by the International 

Standards Organization (ISO 14040 and 14044) [2], and efforts 

have been made in this study to adhere to ISO standards, which 

include stakeholder reviews.

Scope

The 2022 scenario includes 15 billion gallons of corn ethanol, 

assumed to be produced solely by corn dry mills, and 16 billion 

gallons of ethanol from cellulosic feedstocks. The cellulosic 

feedstocks considered are corn stover, wheat straw, 

switchgrass, and forest residues. This study is done on a 

national level. Most data used are national averages and will not 

be indicative of one particular region of the country. All ethanol is 

assumed to be produced in the continental United States, 

precluding the need for imports. All energy flows associated with 

production, distribution, and use of ethanol are tabulated. 

Avoided products, such as the co-product of the corn ethanol 

process, which is used as a substitute for animal feed, are
included. In addition, product displacement, such as the removal 

of corn stover for ethanol resulting in lost winter grazing feed, is 

also included. Impacts from the manufacture and construction of 

infrastructure attributable to EISA is amortized over the lifetime 

of the infrastructure. However, the impacts of land use converted 

as an indirect result of land used for biofuels biomass production, 

so-called “indirect land use” [3] is not included in this phase of 

the study. The science behind indirect land use is still not settled, 

and when a stronger scientific consensus on this issue emerges, 

this LCA will incorporate those results.

The product stages in this life cycle are biomass production, 

harvest, pre-processing, transportation to conversion plant, fuel 

deliver, and end use. Modules were developed in SimaPro 

v.7.1.8 (Product Ecology Consultants, Amersfoort, The 

Netherlands) using the EcoInvent v.2.0 (Swiss Center for Life 

Cycle Inventories, Duebendorf, Switzerland) database for 

materials and processes that were not user-generated. 

Feedstock production and harvest

Feedstock production and harvest includes all activities and 

infrastructure required to establish and grow the biomass, and 

then harvest the feedstock so it is available to ship for 

preprocessing.

Corn and corn stover production is modeled using data from the 

USDA National Agricultural Statistics Service (USDA-NASS) and 

standard US corn production practices. Corn grain yield is 

projected to the year 2022 using least squares regression 

analysis of historical US average corn production data from 1964 

to 2006; a 95% prediction interval (PI) of 9.5 to 12.4 Mg ha-1 is 

used [4]. 

Total stover produced was estimated using a harvest index (HI) 

of 0.5 (HI = weight of corn grain / (weight of corn grain + weight 

of stover) [5]. However, harvested stover is based on a removal 

rate of 30% of the total stover [6]. This removal rate does not 

account for soil carbon maintenance, and is therefore likely an 

optimistic estimate of a national average stover removal rate.

Because corn stover is a co-product of corn production, the 

environmental burdens associated with the whole system (i.e., 

grain and stover production) should be shared between the two.

For this study, environmental burdens between corn grain and 

corn stover are allocated using an incremental allocation. The 

incremental allocation is conceptually the simplest and involves 

assigning only the environmental burdens that are directly a 

result of stover harvesting activities to the stover. Several other 

allocation methods were tested including ones based 

proportionally on mass, energy content, and ethanol yield, but 

the selection of an allocation method was not found to

significantly impact the results. 

Wheat and wheat straw production are modeled similarly to corn 

and corn stover. Two wheat systems are modeled: winter wheat 

and spring wheat. The two systems are similar with regard to 

inputs and management practices. Wheat production is modeled 

using data from the USDA National Agricultural Statistics Service 

(USDA-NASS) and standard US wheat production practices for 

both winter and spring wheat.

Switchgrass production are projected based on a series of 

papers from on-farm studies in North Dakota, South Dakota, 

Nebraska, and Minnesota [7-9]. Since switchgrass production 

does not involve any co-products, all environmental burdens are

assigned to switchgrass.

Forest residue is modeled as a co-product of whole-tree timber 

harvesting operations. For the purpose of this study, forest 

residue is defined as non-merchantable woody material made 

available through standard timber harvesting operations. This 

includes non-merchantable stem, crown, and pre-commercial 

thinnings. Whole-tree harvest is the predominant timber 

harvesting method practiced in the US and involves harvesting 

the entire tree, less the stump and roots, and transporting it to 

the landing where it is processed into merchantable portions 

(i.e., sawlogs and pulpwood) [10]. Life cycle inventory (LCI) data 

for US logging practices are developed by the Consortium for 

Research on Renewable Industrial Materials.

Corn grain harvest consists of combine harvesting, transport to a 

storage facility. All processes are taken from EcoInvent [11]. 

Harvest steps for the herbaceous feedstocks are modeled based 

on the Idaho National Laboratory (INL) feedstock delivery design 

report [12]. 

Preprocessing

The process of preprocessing biomass in 2022 is modeled 

based on the INL feedstock delivery design report [12]. That 

report projects out a feedstock supply system that would provide 

a uniform feedstock prior to arriving at the biorefinery conversion 

facility. In the “Advanced Uniform-Format Feedstock Supply 

System,” the biomass is separated from any grain, ground, and 

stored at a preprocessing facility. This ground biomass is then 

delivered to the plant gate, avoiding feedstock processing at the 

biorefinery. This LCA includes the assumption that this would be 

the feedstock supply system in 2022.

Transport of the harvested feedstock to the preprocessing 

facility, located some distance from the farm, is modeled in this 

section. Transport of the corn grain is divided between wagon 

and a semi-truck transport, with different distances for each 

mode [13]. 

Feedstock transport

Feedstock is transported from the storage facility to the 

conversion facility. The mode of transportation is broken down 

across truck, rail, and barge based on a USDA report [14]. 

Distances are based on the INL design report, Carnegie Mellon 

University Modeling, and the USDA [14-16]. 

Conversion technology

While no commercial-scale cellulosic ethanol facilities exist 

today, conceptual designs for these facilities are documented in 

NREL design reports. Production of ethanol by biochemical route 

(specifically through dilute acid pretreatment, enzymatic 

hydrolysis, and fermentation) is described in a report by Aden et 

al. [17]. Production of ethanol via a thermochemical route 

(through indirect gasification and mixed alcohol synthesis) is 

documented in a report by Phillips et al. [18]. Both these designs 

were constructed for a future scenario when technological 

improvements would make cellulosic ethanol cost competitive. 
For the 2022 scenario in this LCA, these conceptual designs are 

used as the basis for cellulosic ethanol conversion facilities.

This study employs the simplifying assumption that the 

herbaceous feedstocks (corn stover, wheat straw, and 

switchgrass) are converted through a biochemical fermentation 

pathway to ethanol while the woody feedstock (forest residues) 

is converted through a thermochemical gasification pathway to 

ethanol.

Conversion processes are based on models developed using 

AspenPlusTM (Aspen Technology Inc., Burlington, 

Massachusetts, USA) software. For sensitivity analysis in this 

LCA, the models are run for different parameter values and 

linear regressions are developed for inputs and outputs of the 

processes.

Corn dry mill mass balances are based on a 2007 version of the 

corn dry mill AspenPlusTM model used in a joint 2000 report 

between the U.S. Department of Agriculture and NREL [19]. The 

energy input for the corn dry mill is based on a study by Mueller 

of process heat and electricity for corn dry mills [20]. The 2022 

version of the corn dry mill is based on the projection of process 

heat and electricity mix from the Mueller study along with 

increased ethanol yields from Argonne National Laboratory’s 

GREET (Greenhouse gases, Regulated Emissions, and Energy 

use in Transportation) 1.8b (Argonne National Laboratory, 

Argonne, Illinois, USA) model [21]. 

Ethanol distribution

Ethanol is distributed from the conversion plant to a blending 

terminal, where it is blended with gasoline to form E85 

transportation fuel. This fuel is then transported to the refueling 

station. The transportation modal allocation between truck,

barge, and rail is based on studies by USDA and Reynolds [14, 

22]. Gasoline used for blending in 2022 is assumed to be the 

same as gasoline in 2005, since while unconventional crude 

sources, such as tar sands, are expected to increase in 

production by 2022, the impact is still small compared to the 

overall crude supply. Infrastructure needed for E85 delivery is 

included.

End use

Vehicle operation is based on evaluating vehicle types (car, light 

duty truck 1, light duty truck 2) from the GREET model [21]. This 

study considers the use of E85 in a flex-fuel vehicle. Other life 

stages of the vehicle, such as vehicle manufacture, servicing, 

and end-of-life are not included.

RESULTS

A comparison of the GWP of the E85 fuel in 2022 resulting from 

the different feedstocks is shown in FIGURE 1. The graph shows 

the GWP calculated in carbon dioxide equivalents per vehicle 

kilometer traveled. The results span the entire life cycle of the 

fuel, from the production of the biomass to the end use in a 

vehicle.

Each feedstock in FIGURE 1 show the contribution of each 

process stage. The feedstock uptake portion of each bar is 

negative because each feedstock consumes carbon dioxide from 

the atmosphere. 

Because this LCA includes the carbon dioxide taken in by the 

feedstock (biogenic carbon dioxide), the conversion stage has a 

large impact on global warming potential. However, this is mostly 

biogenic carbon dioxide and not fossil carbon dioxide. End use 

also has a significant impact on global warming potential. Similar 

to the conversion stage, the end use stage also includes the 

release of biogenic carbon dioxide from the combustion of 

ethanol. Since this study is on E85, the end use also includes 

combustion of the gasoline portion of the fuel. Feedstock 

production and harvesting for switchgrass has a larger impact 

than with other feedstocks because switchgrass harvest 

efficiency is 80 percent and the switchgrass that is not harvested 

decomposes to produce carbon dioxide [23]. 

FIGURE 1. GWP FOR 2022 E85 ACROSS FEEDSTOCKS

Water use for the different feedstocks for E85 ethanol are shown 

in FIGURE 2. Conversion shows a negative water use for corn 

stover, switchgrass, and wheat straw because electricity from 

lignin is produced, displacing grid electricity and any water use 

used in electricity generation. Corn shows negative water use 

because corn dry mills produce distillers dried grains with soluble 

(DDGS), which substitute for animal feed: namely corn, soy, and 

urea. The displacement of DDGS avoids the water used in 

producing conventional animal feed. Water use in the 

preprocessing stage for corn stover, switchgrass, and wheat 

straw is significant because electricity is used in drying, grinding, 

and dust collection [16]. The water use in this life cycle is not the 

same as consumptive water use, which may be more relevant 

when considering water sustainability issues. Global Warming Potential (kg CO

corn corn stover switchgrass wheat straw forest residue

2e per km traveled)

-1.2

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Feedstock production and harvesting 

Preprocessing 

Feedstock transportation 

Conversion 

Distribution 

Vehicle operation

Feedstock CO2 absorption 

Net emissions
Corn shows the largest amount of water use, the bulk of it 

related to feedstock production. Under the incremental allocation 

method employed in this study, the amount of irrigated water is 

allocated entirely to grain and not to residue. Water use is 

extremely sensitive to the choice of allocation method. While 

there remains considerable debate in the LCA literature as to 

how to assign impacts to co-products, since agricultural residues 

would not likely be the main (most highly valued) agricultural 

product from a multi-product agricultural system, the incremental 

allocation method would appear justified. However, if farmers 

decided to grow a feedstock partly based on residue value 

instead of just based on grain value, the use of the productpurpose allocation method should be re-evaluated and 

sustainability conclusions regarding water should be revisited.

corn corn stover switchgrass wheat straw forest residue

Water Use (L per km traveled)

-5

0

5

10

15

20

Feedstock production and harvesting 

Preprocessing

Feedstock transportation

Conversion

Distribution

Vehicle operation

Net Water

FIGURE 2. TOTAL LIFE CYCLE WATER USE FOR 2022 E85

corn corn stover switchgrass wheat straw forest residue

Net Energy Value (MJ per km traveled)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

FIGURE 3. NET ENERGY VALUE FOR 2022 E85

The net energy value for E85 for the different feedstocks is 

shown in FIGURE 3. Net energy value is calculated by summing 

up the lower heating values of the products (ethanol, gasoline, 

and mixed alcohols) and subtracting the input energies from 

fossil, nuclear, and renewable sources. The energy values of 

avoided products such as DDGS and electricity are not included 

since the life cycle already takes into accounted avoided fossil 

and other input energies.

Almost all the input energy come from fossil sources, and the 

breakdown of the fossil energy is shown in FIGURE 4. 

Distribution constitutes a large portion for each feedstock 

because distribution includes the blending of gasoline and the 

fossil input involved in the production of gasoline. Corn stover, 

switchgrass, and wheat straw have no fossil energy input for 

conversion because the conversion refineries generate their own 

electricity.
corn corn stover switchgrass wheat straw forest residue

Fossil Energy (MJ per km traveled) -0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Feedstock production and harvesting 

Preprocessing

Feedstock transportation

Conversion

Distribution

End use

FIGURE 4. FOSSIL ENERGY FOR 2022 E85

Global warming potential for all feedstocks for E85 are better 

than gasoline in 2005, the standard set in EISA. E85 from corn 

ethanol in 2022 is over 40 percent better in GWP than gasoline 

in 2005. Corn grain ethanol in 2022 has fewer carbon dioxide 

emissions as biomass boilers, biomass combined heat and 

power, and integrated biogas systems make up a larger portion 

of the energy feedstock for corn dry mills. In addition, corn dry 

mills are projected to increase in efficiency.

Cellulosic ethanol in 2022 also has life cycle carbon dioxideequivalent emissions than gasoline. The feedstock used for 

cellulosic feedstock makes a significant impact on the global 

warming potential of ethanol. Among herbaceous cellulosic 

feedstocks, greenhouse gas emissions are all about the same, 

with wheat straw being the least carbon intensive. Wheat straw, 

as a residue, has fewer biomass production-related inputs 

compared to switchgrass, and unlike corn stover, wheat straw 

does not serve as a feed supplement and thus does not require 

a product to displace the loss of wheat straw. Forest residue has 

a higher global warming potential because of the conversion 

process. From a life cycle water and net energy value 

perspective, cellulosic feedstocks are more sustainable than 

corn ethanol in 2022.

CONCLUSION

A life cycle model has been developed to analyze the climate 

impact of the renewable fuel standards set by EISA. Projected 

2022 E85 from corn and cellulosic feedstocks show improved life 

cycle greenhouse gas emissions over gasoline. This model 

provides a framework to better understand the major factors 

affecting greenhouse gas emissions related to the 2022 biofuels 

targets of EISA. Sensitivity and uncertainty analysis will be 

included at a later stage of this study as will indirect land use 

impacts. Current estimates of indirect land use have varied by a 

factor of four [24]. When greater scientific consensus is reached 

on this factor, the indirect land use impact can be included in this 

study.

REFERENCES

1. United States Government, Energy Independence and 

Security Act of 2007, in Public Law 110-140. 2007. p. 

311.

2. Finkbeiner, M., et al., The new international standards 

for life cycle assessment: ISO 14040 and ISO 14044.

International Journal of Life Cycle Assessment, 2006. 

11(2): p. 80-85.

3. Searchinger, T., et al., Use of U.S. Croplands for 

Biofuels Increases Greenhouse Gases Through 

Emissions From Land-Use Change. Science, 2008: p. 

1-7.

4. USDA-NASS, National agricultural statistics service. 

Quick stats. . 2006.

5. Donald, C.M., and Hamblin, J. , The biological yield and 

harvest index of cereals as agronomic and plant 

breeding criteria. Advances in Agronomy, 1976. 28: p. 

361-405.

6. Graham, R.L., et al., Current and potential US corn 

stover supplies. Agronomy Journal, 2007. 99(1): p. 1-

11.

7. Vogel, K.P., et al., Switchgrass Biomass Production in 

the Midwest USA: Harvest and Nitrogen Management.

Agronomy Journal, 2002. 94: p. 413-420.

8. Vogel, K.P., et al., Winter Survival in Switchgrass 

Populations Bred for High IVDMD. Crop Science, 

2002(42): p. 1857-1862.

9. Vogle, K.P., Genetic Improvement of Switchgrass and 

Other Herbaceous Plants for Use as Biomass Fuel 

Feedstock, DOE, Editor. 2000: Oak Ridge, TN. p. 52.

10. Leinonen, A., Harvesting technology of forest residues 

for fuel in the USA and Finland, in Espoo 2004. 2004, 

VTT Processes.

11. Nemecek, T. and T. Kägi, Life Cycle Inventories of 

Agricultural Production Systems Data 2.0, in ecoinvent 

report 2007, Swiss Centre for Life Cycle Inventories: 

Zürich and Dübendorf, Switzerland.

12. Hess, J.R., et al., Uniform-format solid feedstock supply 

system. 2009, Idaho National Laboratory: Idaho Falls, 

Idaho.

13. Yu, T.-H. and C.E. Hart, The 2006/07 Iowa Grain and 

Biofuel Flow Study: A Survey Report. 2008, Center for 

Agricultural and Rural Development, Iowa State 

University: Ames, Iowa.

14. Denicoff, M.R., Ethanol Transportation Backgrounder: 

Expansion of U.S. Corn-based Ethanol from the 

Agricultural Transportation Perspective. 2007, United 

States Department of Agriculture. p. 1-29.

15. Wakeley, H.L., Alternative Transportation Fuels: 

Infrastructure Requirements and Environmental Impacts 

for Ethanol and Hydrogen, in Department of Civil and 

Environmental Engineering. 2008, Carnegie Mellon 

University: Pittsburgh, PA. p. 195.
16. INL, Uniform-Format Feedstock Supply System Design 

for Lignocellulosic Biomass: DRAFT. 2009, Idaho 

National Laboratory: Idaho Falls, ID. p. 134.

17. Aden, A., et al., Lignocellulosic Biomass to Ethanol 

Process Design and Economics Utilizing Co-Current 

Dilute Acid Prehydrolysis and Enzymatic Hydrolysis for 

Corn Stover. 2002, National Renewable Energy 

Laboratory: Golden, CO.

18. Phillips, S., et al., Thermochemical Ethanol via Indirect 

Gasification and Mixed Alcohol Synthesis of 

Lignocellulosic Biomass. 2007, National Renewable 

Energy Laboratory: Golden, CO.

19. McAloon, A., et al., Determining the Cost of Producing 

Ethanol from Corn Starch and Lignocellulosic 

Feedstocks. 2000, U.S. Department of Agriculture 

National Renewable Energy Laboratory: Golden, CO.

20. Mueller, S., An analysis of the projected energy use of 

future dry mill corn ethanol plants (2010-2030). 2007, 

University of Illinois at Chicago: Chicago, IL.

21. Wang, M., The Greenhouse Gases, Regulated 

Emissions, and Energy Use in Transportation (GREET) 

Model 1.8b. 2008, Argonne National Laboratory.

22. Reynolds, R.E., Ethanol's Potential Contribution to U.S. 

Transportation Fuel Pool. 2006, Downstream 

Alternatives Inc.

23. Bransby, D. Energy balance and energy efficiency of 

bioenergy. AFC Cooperative Farming News 2006 

January 2006 [cited 2009 May 11]; Available from: 

http://www.alafarmnews.com/0905archive/0905bioener

gy.htm. 

24. Tyner, W., F. Taheripour, and U. Baldos. Land use 

carbon emissions due to the U.S. ethanol program. 

2009 January 26; Available from: 

http://www.agecon.purdue.edu/staff/tyner/papers/Purdu

e%20Wally%20Farzad%20Uris.pdf. 
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Life Cycle Assessment of the Energy Independence and Security 

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14. ABSTRACT (Maximum 200 Words)

Strategies to reduce the dependence of the United States on foreign oil, increase the use of renewable energy, and 

lessen the contribution to global warming have received significant attention. National adoption of such strategies 

could significantly impact America’s economy and security as well as global climate change. The Energy 

Independence and Security Act of 2007 (EISA) mandates specific renewable energy market penetration targets for 

the year 2022 [1]. For liquid transportation fuels, the 2022 EISA mandate is 36 billion gallons per year (bgy) of 

biofuel, of which 21 bgy must come from feedstocks other than corn starch. Despite this legal mandate for renewable 

biofuels, many questions remain unanswered with regard to the potential environmental effects of such a large 

increase in the production and use of biofuels. In addition to specifying volumetric standards for these renewable 

fuels, EISA establishes greenhouse gas mitigation standards. The objective of this study is to use life cycle 

assessment (LCA) to evaluate the global warming potential (GWP), water use, and net energy value (NEV) 

associated with the EISA-mandated 16 bgy cellulosic biofuels target, which is assumed in this study to be met by 

cellulosic-based ethanol, and the EISA-mandated 15 bgy conventional corn ethanol target. Specifically, this study 

compares, on a per-kilometer-driven basis, the GWP, water use, and NEV for the year 2022 for several biomass 

feedstocks. 

15. SUBJECT TERMS

life-cycle assessment; ethanol; global warming potential; Energy Independence and Security Act; DISA; greenhouse 

gas; biofuels; transportation

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