Supporting information for:
Impacts of co-location, co-production and process energy source on life cycle energy use
and greenhouse gas emissions of lignocellulosic ethanol
Jon McKechnie, Department of Civil Engineering, University of Toronto, Toronto, Canada
Yimin Zhang, National Renewable Energy Laboratory, Golden CO
Akifumi Ogino, National Agriculture and Food Research Organization, Tsukuba, Ibaraki, Japan
Brad Saville, Department of Chemical Engineering and Applied Chemistry, University of
Toronto, Toronto, Canada
Sylvia Sleep, Department of Civil Engineering, University of Toronto, Toronto, Canada
Mark Turner, Mascoma Canada Inc., Georgetown, Canada
Robert Pontius, Mascoma Canada Inc., Georgetown, Canada
Heather L. MacLean, Department of Civil Engineering, Department of Chemical Engineering
and Applied Chemistry, University of Toronto, Toronto, Canada
Corresponding author: Heather L. MacLean, Department of Civil Engineering, University of
Toronto, Canada, M5S 1A4
Email: hmaclean@ecf.utoronto.ca
S.1 METHODS
S.1.1 Feedstock production, collection, and transportation
Inputs to hybrid poplar (hereafter referred to as “poplar”) production and associated GHG
emissions are modeled as reported in GREET 1.8bS1 as farmed tree biomass production.
Relevant energy use and greenhouse gas (GHG) emission data for all stages of poplar provision
(cultivation through to delivery to the cellulosic ethanol production facility) is presented in Table
S-1. The current study does not include land use change (LUC) impacts of poplar production.
The direct LUC credit attributed to carbon sequestration in poplar plantations within the GREET
model is therefore removed.
Table S-1. Energy use and GHG emissions associated with poplar production and delivery.
Poplar
farming
Energy use (g
per dry Mg) 1
Fossil
Petroleum
341
279
Life cycle emission stage
Fertilizer and
N2O
herbicide
emissions
Poplar
production and from nitrogen transportation
transportation
fertilizer
51
7
-
333
303
Total, poplar
production and
delivery
725
584
1
Emissions 1 (g
per dry Mg)
CH4
30
4
28
2
N2O
0
1
16
1
CO2
25,831
3,213
24,754
Notes: 1. Data from GREET 1.8b.S1 2. Zero value due to rounding.
62
19
53,798
S.1.2 Poplar conversion to ethanol
Figure S-1 shows the process of ethanol production from input poplar. Input poplar undergoes
uncatalyzed steam explosion pretreatment. Enzymes are input to the hydrolysis stage to convert
cellulose and hemicelluloses to C5 and C6 sugars. Following fermentation and distillation,
residual biomass is further processed. Uses of residual biomass differ by ethanol production
scenario, being: employed to provide process energy for ethanol production; to produce excess
electricity or steam for export; and/or to produce fuel pellets. Upstream energy use and
associated emissions for poplar production and delivery are reported above. Ongoing
development of cellulase technology prevents accurate estimation of enzyme inputs and
associated upstream impacts. Enzyme inputs are therefore not included in this study, despite the
potential contribution to ethanol life cycle emissions and energy use.S2 Energy and inputs
required for co-product production are included within in the ethanol production stage.
Figure S-1. Flowchart of ethanol production from poplar.
2
3
S.1.3 Co-location, process energy, and co-product scenarios
We consider a range of ethanol plant configuration scenarios, differing by co-location (standalone, adjacent to steam-consuming facility, adjacent to steam and/or electricity exporting
facility), process energy source (generation on-site from residual biomass, import of grid
electricity, on-site steam production from natural gas, import of steam and/or electricity from
adjacent facility), and co-product (electricity, pellets, steam). Ethanol plant operations data is
presented in Table 1 of the main text.
S.1.3.1 Process energy sources
Process energy requirements for ethanol and co-product production are provided by Mascoma
and reported in Table 1 of the main text. Associated energy use and GHG emissions for the
various process energy sources are reported in Table S-2. Non-CO2 GHG emissions resulting
from residual biomass combustion are estimated based on GREET 1.8b for farmed tree biomass
combustion in small boiler. Steam production from natural gas assumes a boiler efficiency of
85%. Upstream energy use and GHG emissions related to natural gas production and delivery,
as well as GHG emissions during steam production, are modeled based on reported values in
GREET 1.8b. Imported electricity is assumed to be U.S. Midwest grid average. The mix of
electricity generation sources in MidwestS3 is input to GREET to determine GHG emissions
associated with the average electricity mix.
Two scenarios (“3-steam, electricity” and “3-steam”) assume all or a portion of process energy is
imported from an adjacent facility, modeled based on a pulp mill. Scenario “3-steam,
electricity” assumes the pulp mill employs black liquor gasification and provides both steam and
electricity for export. With gasification, pulp mills produce excess electricity for export. NonCO2 GHG emissions from black liquor gasification modelled based on electricity generation in
the GREET biomass gasification turbine pathway. Waste steam from electricity generation via
gasification is assumed to be used within the pulp mill.S4 To provide steam to the ethanol
facility, we assume that a portion of syngas produced from black liquor is diverted to a boiler.
Efficiency of steam generation is determined through a series of back-calculations of efficiencies
reported in GREET, all assuming equal efficiency electricity and steam generation from syngas
and natural gas. The biomass gasification turbine pathway reports electricity generation
4
efficiency of 40% compared to 53% for a natural gas turbine; this indicates a 75% biomass
gasification efficiency. Steam generation from natural gas is assumed to be 85% efficient;
applying this to the biomass pathway results in an overall efficiency of 63% for converting
biomass to steam via gasification. The final scenario, “3-steam”, assumes the pulp mill employs
black liquor combustion, producing excess steam that would be available for export. We treat
this excess steam as a waste product of pulping chemical recovery and electricity generation at
the pulp mill; therefore associated emissions are attributed to the pulp mill.
Table S-2. Process energy sources: associated energy use and GHG emissions.
Parameter
Value
Residual biomass
Characteristics
Energy content (GJ/dry Mg)
Combustion energy use and emissions
(MJ or g per GJ biomass)
Fossil energy
Petroleum energy
Data source and notes
20.0
0
0
CH4
N2O
CO2
3.63
10.43
01
Natural gas (steam generation)
Characteristics
Steam production efficiency
85%
Upstream energy use and emissions (kJ
or g per GJ natural gas)
Fossil energy
Petroleum energy
72,385
4,269
CH4
N2O
CO2
186
0*
4,992
Steam production energy use and
emissions (kJ or g per GJ natural gas)
Fossil energy
Petroleum energy
CH4
N2O
S1
S1
* zero value due to
rounding
1,000,000
0
1
1
5
CO2
56,283
Coal
Petroleum
Natural gas
Other gases
Nuclear
Hydroelectric
Other renewables
Other
70.6 %
0.4 %
4.1 %
1.8 %
20.2 %
0.9 %
2.0%
0.1 %
Based on data from S3
Energy use and emissions (kJ or g per
kWh electricity) 3
Fossil energy
Petroleum energy
9, 014
146
Calculated from S1
Imported Midwest electricity
Generation mix 2
CH4
1
N2O
0*
CO2
891
Imported steam and electricity from adjacent facility
Black liquor gasification
Electricity generation efficiency
40%
Steam production efficiency
63% 4
*
zero value due to rounding
Calculated from S1
Emissions (g/GJ biomass)
CH4
N2O
CO2
4
10
97,022
Black liquor combustion
Treated as waste
product; all emissions
allocated to the
exporting pulp mill
Notes: 1. Biomass is considered to be immediately carbon neutral so biomass-based CO2
emissions are not counted. 2. Midwest consists of 8 states: Illinois, Indiana, Iowa, Michigan,
Minnesota, Missouri, Ohio, and Wisconsin. 3. To match with available GREET electricity
pathways, generation source data is adapted as follows: “petroleum” is modeled as “residual oil”;
“other gases” is modeled in GREET as “natural gas”; additional generation sources not modeled
in GREET are included in the category “other”. Energy use and GHG emissions are then
calculated in GREET by inputting the following generation mix parameters: coal (70.6%);
nuclear (20.2%); natural gas (5.9%); oil (0.4%); and other (3.0%). 4. Steam production
efficiency calculated based on GREET data (description in text).
6
S.1.3.2 Co-products
GHG emissions and energy use associated with co-product production are included in the
“Ethanol Production” stage. For all cases, biomass-based CO2 emissions are assumed to not
increase atmospheric GHGs (biomass is immediately “carbon neutral”).
Excess electricity is exported to the U.S. Midwest grid and is assumed to displace grid-average
electricity. The sensitivity analysis considers the impact of displaced electricity GHG intensity
on life cycle GHG emissions. Non-CO2 GHG emissions from lignin combustion are estimated
as farmed tree combustion in small biomass boiler in GREET.S1 Co-product pellets are assumed
to be co-fired with coal in retrofit coal generation stations; in the Sensitivity Analysis, we
consider the use of pellets to displace natural gas. Transport distance between ethanol facility
and coal generating station is estimated as 160 km (100 miles). Pellets are shipped by heavy
duty diesel truck; associated energy use and GHG emissions data are extracted from GREET
1.8b.S1 Pellet combustion at coal generating stations is assumed to not incur any loss of
generation efficiency (i.e., pellets displace an equivalent quantity of coal based on energy
content). GHG emissions and energy use related to combustion of pellets and coal at the GS,
and upstream activities related to coal production and delivery, are modeled using data from
GREET 1.8b. Steam generation from residual biomass uses data from GREET for farmed tree
biomass combustion in a small boiler to estimate non-CO2 GHG emissions. We assume steam
production that is displaced in the adjacent energy importing facility would have been produced
from natural gas (85% efficiency). Energy use and associated GHG emissions data for the coproduct options and displaced products are shown in Table S-3.
Table S-3. Energy use and associated GHG emissions of co-products and displaced products
Parameter
Co-product electricity
Displaced grid average electricity
Energy use and emissions (kJ or
g per kWh electricity)
Value
Data source and notes
As reported in Table S2 for imported Midwest
electricity
Co-product pellets
Pellet transportation
Mode Heavy duty diesel truck
Distance (km)
160
7
Energy use and emissions (MJ
or g per dry Mg pellet)
Fossil energy
Petroleum energy
CH4
N2O
CO2
Pellet combustion
Fossil fuel substitution
efficiency
463
420
S1
39
1
34,380
100%
Pellet combustion emissions (g
per GJ pellet)
CH4
N2O
CO2
Displaced coal
Energy use and emissions (MJ
or g per GJ) 2
Fossil energy
Petroleum energy
CH4
N2O
CO2
4
10
01
S1
1,020
14
S1
114
1
104,239
Displaced natural gas
Energy use and emissions (MJ
or g per GJ) 2
Fossil energy
Petroleum energy
1,072
4
CH4
N2O
CO2
187
1
61,275
Co-product steam
Displaced steam generation
Fuel source
Steam production efficiency
Energy use and emissions (MJ
or g per GJ) 1
S1
Natural gas
85%
As reported above for
displaced natural gas
8
S.1.4 Fuel use in light-duty vehicle
Ethanol is denatured with gasoline (2.75%) before blending to E85 fuel (blend of 85% denatured
ethanol; 15% gasoline). This results in an E85 volumetric ethanol content in of 82.9%. Gasoline
in 2015 is assumed to be a mixture of conventional (35%) and reformulated (65%). Energy use
and GHG emissions during the vehicle operation stage are reported in Table S-4.
Table S-4. Vehicle operation: energy use and associated GHG emissions
Parameter
Ethanol (blended as E85 fuel)
Fuel economy
Value
Data source and notes
10.1 Lgasoline equivalent/100 S1
km
Energy use and emissions (kJ or g per
km driven)
Fossil energy
Petroleum energy
772
772
CH4
N2O
CO2
0*
0*
39 1
Gasoline
Fuel economy
10.1 L/100 km
Energy use and emissions (kJ or g per
km driven)
Fossil energy
Petroleum energy
CH4
N2O
CO2
* zero value due to
rounding
S1
3,125
3,125
0*
0*
234
* zero value due to
rounding
Notes: 1. Biomass based CO2 emissions are not counted.
9
S.2. RESULTS
The California Low Carbon Fuel Standard requires fuel GHG intensity be reported in terms of
gCO2eq/MJ of fuel. Results from the present study are presented in this format in Table S-5.
Table S-5. Well-to-wheel (WTW) results for ethanol pathways and reference gasoline pathway,
reported in terms of gCO2eq/MJ
Production scenarios
Life cycle
stage
WTT,
ethanol
WTT,
gasoline
Vehicle
operation 1
Total
WTW
emissions
1Electricity
1-Pellet
1-Max
Pellet
2-Steam
3-Steam,
electricity
gCO2eq/MJ
3-Steam
GREET
ethanol2
GREET
gasoline3
-13.2
-25.7
-45.7
-8.7
-86.4
-75.5
2.4
-
5.1
5.1
5.1
5.1
5.1
5.1
5.1
21.4
12.8
12.8
12.8
12.8
12.8
12.8
12.8
73.5
4.7
-7.8
-27.8
9.2
-68.5
-55.6
20.3
95.0
Notes: 1. Includes credit for biogenic carbon content of ethanol. 2. GREET ethanol is default
farmed tree-to-ethanol pathway (Version 1.8b, NREL conversion process with electricity coproduct displacing average Midwest grid generation). 3. GREET gasoline is expected
composition in 2015 (35% conventional, 65% reformulated gasoline)
S.2.1 Ethanol yield and GHG emissions
Improved GHG emission performance accompanying lower ethanol yield results from two
factors: with lower ethanol production, more residual biomass is available for co-products,
increasing the co-product credit; and this co-product credit is divided over a smaller output of
ethanol. To disaggregate the contribution of these two factors, we calculate GHG emissions on
the basis of one dry Mg of poplar. Table S-6 shows results on this basis for the “1-Pellet”
scenario wherein a portion of residual biomass is combusted on site to provide process steam and
electricity, with the remaining residual biomass pelletized and utilized off-site to displace coal.
The trend of greater emission reductions with lower ethanol yield remains from the perspective
of GHG emissions per Mg poplar. As reported elsewhere,S5 biomass-based solid fuels displacing
coal provide a greater GHG reduction than producing liquid fuels (e.g., ethanol) to displace
gasoline. This is primarily due to the carbon intensity of the displaced fuel (coal is more carbonintensive than gasoline). With lower ethanol yields more of the input biomass is allocated to the
co-product pellet stream, resulting in greater GHG emission reductions.
10
Table S-6. GHG emissions for ethanol production scenario “1-Pellet” employing functional unit
of one dry Mg poplar.
Low ethanol yield
Parameter
Poplar production
Poplar
transportation
Ethanol production
Co-product credit
Ethanol transport
and distribution
Upstream gasoline
Vehicle operation
Total WTW
Displaced gasoline
TOTAL
35,416
25,737
Base case ethanol
High ethanol yield
yield
gCO2eq./Mg poplar (dry)
35,416
35,416
25,737
25,737
19,179
- 554,527
7,374
18,724
- 315,048
9,673
18,345
- 146,024
11,306
34,204
85,323
- 347,294
- 618,009
- 965,304
44,868
111,924
- 68,708
- 810,684
- 879,392
52,446
130,828
128,054
- 947,610
- 819,556
Given the limited availability of land for bioenergy production, it is important to consider GHG
emissions reductions on the basis of land area dedicated to biomass production (e.g.,
gCO2eq/ha/yr). This is the product of GHG emissions per unit of biomass input (gCO2/Mg) and
biomass yield (odt/ha/yr). In the current study, we employ general assumptions regarding poplar
production under ‘average’ U.S. conditions as the primary focus is on ethanol production
decisions. Without taking into account possible variations in biomass yield (e.g., due to biomass
feedstock selection, genetic stock selection, location, and intensity of agricultural inputs), GHG
emissions assessed on a per unit area basis are proportional to GHG emissions assessed on a per
unit biomass input basis and would be similarly affected by ethanol yield. Depending on
production location within the U.S. and other factors, poplar yield has been reported to vary from
7.3 to 13.5 Mg/ha/yr.S6 Assuming a mean poplar yield of 10.4 Mg/ha/yr, the ‘low ethanol yield’
scenario would result in GHG emissions of -10.0 MgCO2eq/ha/yr; the ‘base case ethanol yield’
scenario would result in GHG emissions of -9.2 MgCO2eq/ha/yr; and the ‘high ethanol yield’
scenario would result in GHG emissions of -8.5 MgCO2eq/ha/yr. Future work incorporating
biomass production decisions could expand on the existing framework to allow for a
comprehensive assessment of land use effectiveness for reducing GHG emissions and energy
use.
11
S.2.2 WTW fossil energy use
Fossil energy use for the ethanol production scenarios and reference gasoline pathway is shown
in Figure S-2. Petroleum energy use for all ethanol scenarios, resulting primarily from the
gasoline content of blended E85 fuel, is significantly reduced compared to gasoline. Total fossil
energy use, the balance of fossil inputs to ethanol and co-product production and credits due to
co-products displacing fossil fuels, is near zero or negative for the ethanol scenarios. Import of
primarily non-fossil or waste process energy results in negative WTW fossil energy use for
ethanol production.
Figure S-2. Well-to-wheel (WTW) fossil energy use.
S.2.3 Comparison with GREET biochemical farmed tree to ethanol pathway
The default GREET pathway for biochemical ethanol production from farmed trees provides the
reference NREL model comparison. We adjust the several input values in GREET for
consistency with the Mascoma pathways: the year of analysis is set to 2015; direct land use
change emissions are set to zero (GREET does not include indirect land use change impacts);
12
and the electricity generation mix is adjusted to the Midwest average calculated in the current
study (reported in Table S-3). All other inputs remain “as-is”.
S.2.4 Sensitivity Analysis
The sensitivity analysis considers the GHG intensity of imported electricity for ethanol
production and electricity displaced by co-product electricity exported from the ethanol facility,
inclusive of both upstream operations (e.g., fuel production, transportation) and electricity
generation. GHG emissions data for natural gas boiler and coal generation facilities are
extracted from GREET 1.8b.S1 GHG emissions associated with electricity generation from
natural gas combined cycle facility are from Zhang et al.S7
We consider the sensitivity of results for pellet co-product scenarios to the fossil fuel that pellets
displace. Displacing natural gas with pellets provides a much smaller co-product credit due
primarily to the lower carbon content of natural gas compared to coal. This reduces the GHG
mitigation performance of ethanol where pellets are produced as a co-product. For all scenarios
investigated here, however, ethanol significantly reduces GHG emissions relative to gasoline
regardless of whether pellets displace coal or natural gas (Figure S-3).
13
Figure S-3. Sensitivity of life cycle GHG emissions to fuel displaced by pellets. NG = natural
gas.
14
S.3 LITERATURE CITED
S1. Argonne National Laboratory, The Greenhouse Gases, Regulated Emissions, and Energy
Use in Transportation (GREET) Model. Version 1.8b. Argonne, IL (2010).
http://www.transportation.anl.gov/modeling_simulation/GREET/index.html [accessed 29
November 2010].
S2. MacLean, HL, Spatari, S, The contribution of enzymes and process chemicals to the life
cycle of ethanol. Environ. Res. Lett. 4:10 pages (2009).
S3. US Energy Information Administration . Annual Energy Outlook 2010. Report # DOE/EIA0383(2010). Washington, DC (2010).
S4. Consonni, S, Larson, ED, Kreutz, TG, Berglin, N, Black liquor gasifier/gas turbine
cogeneration. Trans. ASME. 120:442-449 (1998).
S5. McKechnie, J, Colombo, S, Chen, J, Mabee, W, and MacLean, HL, Forest bioenergy or
forest carbon? Assessing trade-offs in greenhouse gas mitigation with wood-based fuels.
Environ. Sci. Technol. In Press.
S6. Walsh, M, De La Torre Ugarte, DG, Shapouri, H, Slinsky, SP, Bioenergy crop production in
the United States. Environ. Resource Econ. 24:313-333 (2003).
S7. Zhang, Y, McKechnie, J, Cormier, D, Lyng, R, Mabee, W, Ogino, A, MacLean, HL, Life
cycle emissions and cost of producing electricity from coal, natural gas, and wood pellets in
Ontario, Canada. Environ. Sci. Technol.. 44:538-544 (2010).
15