ELECTRONIC SUPPLEMENTARY MATERIAL
This supplementary information document was organized to support the main article, and
contains the following sections:
Section
A
Data Collection and Estimation
B
Methyl Ethylene Glycol (MEG) Synthesis Process
C
PTA 1 Synthesis through Muconic Acid Pathway
D
PTA 2 Synthesis through Isobutanol Pathway
E
PTA 3 Synthesis through Benzene Toluene Xylene Pathway
F
Polyethylene Terephthalate Resin Production
G
Sensitivity Analysis for Energy Input
H
Completeness Check
I
Consistency Check
J
Uncertainty Analysis - Pedigree Matrix
K
Additional References
S-1
A- Data Collection and Estimation
Literature data and patent data were used. In addition, some estimation based on similar chemical
reactions and material processes were used. Therefore, the need to select appropriate benchmark
processes was inevitable. Table S-1 shows the order of priority for selecting the appropriate
benchmark processes for this study. Each benchmark process used was selected in accord with
these priorities.
Table S-1. The order of priority for selecting the appropriate benchmark processes.
1. Chemical reaction process
Same
Similarity
Almost the same
Slightly different
2. Output material
Same
Almost the same
Slightly different
Different
3. Input material
Same
Almost the same
Slightly different
Different
Different
The reason that the use of the same chemical reaction process had the highest priority
was that the type of chemical production process is heavily dependent on the type of chemical
reaction. When operational energies were estimated from these benchmark processes, they were
estimated as proportional to the output materials’ weight. This is because the energy required to
operate chemical production processes is typically much larger than the energy involved in the
chemical reaction itself. For instance, dehydration of ethanol is an example. This stoichiometry
can be written as follows:
𝐶2 𝐻5 𝑂𝐻 → 𝐶2 𝐻4 (𝑒𝑡ℎ𝑦𝑙𝑒𝑛𝑒) + 𝐻2 𝑂, ∆𝐻𝑓 = 42.91(𝑘𝐽/𝑚𝑜𝑙)
When1 kg of ethylene was produced, this system requires 1.54 MJ of energy (= 1000 g ÷
28 g/mol × 42.91 kJ/mol × 0.001 MJ/kJ), theoretically. However, it was reported that 7.4 MJ of
energy is required to operate this system, which is much higher than that of the theoretically
estimated reaction energy demand. This difference seems to come from the operational energy to
run the process. Since each target process was assumed to follow the same chemical reaction
process as the benchmark, operational energies, which were dominant in each production step,
were estimated as proportional to the output materials’ weight. For material amounts (input and
S-2
other byproducts in a unit process), the amounts were estimated based on the stoichiometry of
those processes.
B- Methyl Ethylene Glycol (MEG) Synthesis Process
B-1. Bio-Ethanol Production MEG Synthesis Step 1
As previously described in the main text, all three scenarios include the same MEG
synthesis processes. A raw material, which has a C6 structure such as a starch or sugar crop, is
produced. Raw materials are converted into C6 sugar by fractionation and hydrolysis, and then
converted to ethanol by fermentation. Obtained ethanol is dehydrated into ethylene, and then
oxidized and hydrated into MEG. MEG is used in condensation polymerization in order to
produce bottle grade PET resin.
In this study, corn (technically the glucose in the corn) harvested in the U.S. is
fractionated and goes through hydrolysis and fermentation to be converted into ethanol. The
following equation shows the stoichiometry of this process.
𝐶6 𝐻12 𝑂6 → 2𝐶2 𝐻5 𝑂𝐻 (𝑒𝑡ℎ𝑎𝑛𝑜𝑙) + 2𝐶𝑂2
Obtained ethanol is then purified to increase its concentration. Table S-2 shows the inputs and
outputs for this process. Flow values are for 1 kg ethanol production. In this study, all material
weight and energy balances were checked based on the law of conservation of mass and energy,
which is consistent with the stoichiometry.
S-3
Table S-2. Input/output flows for 1 kg of bio-ethanol
Input
Corn, at farm/US with US electricity
Tap water, at user/CH with US electricity
Sulphuric acid, liquid, at plant/RER with US electricity
Soda, powder, at plant
Ammonium sulphate, as N, at regional storehouse
Diammonium phosphate, as N, at regional storehouse
Heat, natural gas, at industrial furnace > 1000kW
Electricity, medium voltage, at grid/US
3.226 kg
4.224 kg
0.024 kg
0.036 kg
0.010 kg
0.010 kg
4.635 MJ
0.143 kWh
Output
Carbon dioxide, biogenic
Heat, waste
Treatment, sewage, from residence, to wastewater treatment, class
Bio-ethanol
2.526 kg
3.385 MJ
0.001 m3
1 kg
Note: Data was obtained from Ethanol, 99.7 % in H2O, from biomass, at distillation/kg/US (from
Ecoinvent) (For the production of 1 kg of purified ethanol). Ethanol 95 % was subtracted from
the Ethanol, 99.7% unit process by using the Ethanol, 95 % in H2O, from corn, at distillery/US U
(from Ecoinvent) (For the production of 1 kg of ethanol 95 % in H2O). This procedure was
necessary since the subsequent process (MEG synthesis step 2) required 99.7 % ethanol for its
input material. All transportation-related and facility-related parts in the input were excluded.
This same approach was used in all other steps, even if not explicitly mentioned..
S-4
B-2. Ethylene oxide production (MEG Synthesis Step 2)
Ethanol is then converted into ethylene by a dehydration process, as shown in the following
equation.
𝐶2 𝐻5 𝑂𝐻 →
𝐶2 𝐻4 (𝑒𝑡ℎ𝑦𝑙𝑒𝑛𝑒) + 𝐻2 O
Obtained ethylene is then converted into ethylene oxide by oxidation.
2 𝐶 2 𝐻4 + 𝑂 2
→
2𝐶2 𝐻4 𝑂(𝑒𝑡ℎ𝑦𝑙𝑒𝑛𝑒 𝑜𝑥𝑖𝑑𝑒)
The data for this process was obtained from an existing database, Ethylene oxide, at
plant/RER with US electricity U (from US-EI). Since the ethylene oxide process has ethanol data
as an input stream, we replaced that data with the bio-ethanol data obtained from the previous
step in order to obtain Table S-3, which shows the inputs and outputs for this process.
Table S-3. Input/output flows for 1 kg of bio-ethylene oxide
Input
Oxygen, liquid, at plant/RER with US electricity
Electricity, medium voltage, production UCTE at grid/UCTE with US
electricity
Bio-ethanol
Output
Carbon dioxide, fossil
Carbon monoxide, fossil
Ethene (ethylene)
Ethylene oxide
Heat, waste
Methane, fossil
NMVOC, non-methane volatile organic compounds, unspecified origin
BOD5, Biological oxygen demand
COD, Chemical oxygen demand
DOC, Dissolved organic carbon
TOC, Total organic carbon
Disposal, catalyst base Eth. Oxide prod., 0% water, to residual material
landfill/CH with US electricity
Bio-ethylene oxide
S-5
0.463 kg
0.33 kWh
0.825 kg
0.21 kg
1.1 x 10-4 kg
2.3 x 10-4 kg
2.0 x 10-5 kg
1.2 MJ
7.5 x 10-5 kg
2.4 x 10-4 kg
1.9 x 10-4 kg
1.9 x 10-4 kg
2.0 x 10-4 kg
2.0 x 10-4 kg
5.0 x 10-4 kg
1.0 kg
B-3. Mono ethylene glycol production (MEG Synthesis Step 3)
Ethylene oxide is then converted into mono ethylene glycol (MEG) by a hydration process, as
shown in the following equation.
𝐶 2 𝐻4 𝑂
+ 2𝐻2 𝑂 → 2𝐶2 𝐻6 𝑂2 (𝑀𝐸𝐺)
The process of Ethylene glycol, at plant/RER with US electricity U (from US-EI) was used.
Ethylene oxide data in the input was replaced with bio-ethylene oxide data from MEG synthesis
step 2, in order to obtain Table S-4.
Table S-4. Input/output flows for 1 kg of bio-MEG
Input
Water, cooling, unspecified natural origin/m3
Bio-ethylene oxide
Bio-ethanol
Heat, natural gas, at industrial furnace >100 kW/RER
Electricity, medium voltage, production UCTE, at grid/UCTE with US
electricity
Output
Heat, waste
Ethylene oxide
Ethanol
Carbon dioxide, fossil
BOD5, Biological oxygen demand
COD, Chemical oxygen demand
DOC, Dissolved organic carbon
TOC, Total organic carbon
Bio-MEG
0.024 m3
0.05146 kg
0.538 kg
2.0 MJ
0.333 kWh
1.199 MJ
2.619 x 10-3 kg
2.739 x 10-3 kg
9.245 x 10-2 kg
9.16 x 10-3 kg
9.16 x 10-3 kg
2.86 x 10-3 kg
2.86 x 10-3 kg
1.0 kg
C- PTA 1 Synthesis through Muconic Acid Pathway
PTA 1- Synthesis Step 1. Muconic acid Production
In this PTA scenario, lignin is fermented and degraded to muconic acid as shown in the
following reaction.
𝑙𝑖𝑔𝑛𝑖𝑛 → (𝑓𝑒𝑟𝑚𝑒𝑛𝑡𝑎𝑡𝑖𝑜𝑛) →
𝐶6 𝐻12 𝑂4 (𝑚𝑢𝑐𝑐𝑜𝑛𝑖𝑐 𝑎𝑐𝑖𝑑) + 𝐶𝑂2
S-6
This process is not available in databases, so it was estimated based on data from Van
Duuren et al. (2010) for production of adipic acid from biomass via hydrogenation of muconic
acid. The portion of their data from feedstock through fermentation to muconic acid was used.
Van Duuren reported on a variety of potential feedstocks; we selected lignin from wheat stover
as the feedstock for this study. Table S-5 shows the demands/emissions for the production of
1000 kg adipic acid in their study.
Table S-5. Demands/emissions for the production of 1000 kg of adipic acid
Demand/emissions
Phenol (lignin) feedstock, wheat stover
Bioreactor (fermentation)
CED, GJ
7.710
0.240
CO2, kg
9.550
0.010
N2O, kg
2.660
0
The Cumulative Energy Demand (CED) used as input for the fermentation step in this
study was replaced with electricity, gasoline, and diesel data. Energy required for biomass
conversion can be divided into two stages, cultivation and processing. According to Brehmer
(2008), 19.6% of energy is typically from electricity, and the rest was thermal energy from fuel.
Since the study did not describe the fuel composition used in the cultivation stage, we referred to
the LCI data for wheat straw from Ecoinvent (“Wheat straw, at field/kg/US”) in order to estimate
the fuel composition as 16% gasoline and 83.9% diesel. This energy ratio was substituted for the
lignin CED value, which means 19.6% (1.512 GJ) was electricity, 12.9% (0.995 GJ) was
gasoline, and 67.5% (5.203 GJ) was diesel. The CED demand for the bioreactor (fermentation)
was replaced with electricity, as no information about its makeup could be found.
In addition, feed materials for bacterial growth shown in Table S-6 were required. Van
Duuren et al. (2011) used only CED data, which means only energy-related emissions were
included and other impacts such as acidification and eutrophication were ignored. Therefore, USEI LCI data for the appropriate amounts of ammonium sulphate, sodium phosphate, sodium
hydroxide, and hydrochloric acid were incorporated. Data for potassium phosphate and glucose
were not available, so the CED data and the CO2/N2O emission data from Van Duuren et al.
were used (potassium phosphate, CED 0.26 GJ and CO2 10.66 kg; glucose, CED 3.62 GJ, CO2
221.26 kg and N2O:10.14 kg). In the absence of other information, the U.S. electricity mix was
substituted for the CED values for these compounds.
S-7
Table S-6. Feed demands for bacterial growth in the bioreactor, for production of 1000 kg
of adipic acid
Feedstock
Ammonium sulphate
Potassium phosphate
Glucose
Sodium hydroxide
Hydrochloric acid
Amount
0.070 ton
0.090 ton
0.440 ton
0.560 ton
0.540 ton
Adipic acid is made by hydrogenation of muconic acid:
𝐶6 𝐻6 𝑂4 (𝑚𝑢𝑐𝑜𝑛𝑖𝑐 𝑎𝑐𝑖𝑑) +
2𝐻2
→
𝐶6 𝐻10 𝑂4 (𝑎𝑑𝑖𝑝𝑖𝑐 𝑎𝑐𝑖𝑑)
The weight of muconic acid required to produce 1000 kg of adipic acid therefore is 972 kg (=
1000 kg ÷ 146 g/mol × 142 g/mol). This factor was used to calculate the values in Table S-7, for
production of 1 kg muconic acid.
Table S-7. Input/Outputs flows for 1 kg of muconic acid
Input
Electricity, medium voltage, production UCTE, at grid/UCTE with US
electricity
Gasoline, combusted in industrial equipment/US
Diesel, combusted in equipment/US
Hydrogen
Ammonium sulphate
Sodium phosphate
Sodium hydroxide
Hydrochloric acid
Output
Carbon dioxide
Nitrous oxide
Muconic acid
5.794 MJ
0.030 L
0.144 L
0.028 kg
0.07202 kg
0.051 kg
0.576 kg
0.556 kg
0.723 kg
0.013 kg
1 kg
PTA 1- Synthesis Step 2. Cyclohexa-2,5-diene-1,4-dicarboxylate Production
Muconic acid is then converted into cyclohexa-2,5-diene-1,4-dicarboxylate using a Diels-Alder
process, as described in U.S. patent 2011/0124911 A1 (2011). Muconic acid and acetylene are
charged in a lab scale Parr reactor, and the reactor is then heated to 200℃ and held at this
S-8
temperature for 12 hours. An initial pressure of 3.5 MPa is applied. The following equation
shows the stoichiometry of this process.
𝐶 6 𝐻6 𝑂 4 + 𝐶 2 𝐻2 →
𝐶8 𝐻8 𝑂4 (Cyclohexa − 2,5 − diene − 1,4 − dicarboxylate)
Since LCI data for this process are not available, the benchmark process used for
estimation was production of cyclohexane from benzene. Zhang (2008) compared the inputs and
emissions for the production of cyclohexane by solvent-based production and vapor phase
industrial production. In this LCA study, LCI data were estimated from Zhang’s vapor phase
industrial process data. Table S-8 shows the input and output data for the production of 1 kg of
cyclohexane using a vapor phase industrial process.
Table S-8. Cyclohexane production data
Input
Benzene
Hydrogen
Steam
Electricity
Catalyst
0.93 kg
0.078 kg
0.1 kg
0.041 kWh
6.2 x 10-5 kg
Output
Benzene
Hydrogen
Catalyst
Cyclohexane
4.7 x 10-4 kg
1.5 x 10-6 kg
6.2 x 10-5 kg
1 kg
To estimate LCI data for the Diels-Alder process for the production of C8H8O4, the
energy required for the operation was estimated as proportional to the output materials’ weight
ratio (in this case, the ratio was based on the relative mass of cyclohexa-2,5-diene-1,4dicarboxylate and cyclohexane). The required material amounts for the chemical reaction were
calculated on the basis of stoichiometry. This same approach was used in all other steps, even if
not explicitly mentioned. Table S-9 shows the inputs and outputs production of 1 kg cyclohexa2,5-diene-1,4-dicarboxylate production. Since there no bio-based LCI data was available for
acetylene, we used the petrochemical based LCI data available in the US-EI database.
S-9
Table S-9. Input/Output flows for 1 kg of cyclohexa-2,5-diene-1,4-dicarboxylate
Input
Electricity, medium voltage, production UCTE, at grid/UCTE with US
electricity
Steam, for chemical processes, at plant/RER with US electricity
Muconic acid
Acetylene, at regional storehouse/CH with US electricity
Output
Muconic acid
Acetylene, at regional storehouse/CH with US electricity
Cyclohexa-2,5-diene-1,4-dicarboxylate
0.041 kWh
0.10 kg
0.845 kg
0.155 kg
4.27 x 10-4 kg
2.981 x 10-6 kg
1 kg
PTA 1- Synthesis Step 3. Purified Terephthalic Acid Production
Cyclohexa-2,5-diene-1,4-dicarboxylate is then converted into TPA using dehydrogenation as
described in patent US. 2011/0124911 A1 (Burk et al, 2011). According to this patent,
subsequent exposure to air or oxygen rapidly converts cyclohexa-2,5-diene-1,4-dicarboxylate to
TPA. The following equation shows the stoichiometry of this process.
2𝐶8 𝐻8 𝑂4
+ 𝑂2
→ 2𝐶8 𝐻6 𝑂4 (𝑇𝑃𝐴) + 2𝐻2 𝑂
Since LCI data for this process are not available, the benchmark process of dehydrogenation of
xylene to TPA and its purification to PTA was used for estimation. The required energy was
estimated as proportional to the output materials’ weight ratio. The material amounts were
estimated based on the stoichiometry. The water mass generated in the chemical reaction was
excluded because of its insignificant contribution to environmental impacts. This same approach
for water was used in all other steps, even if not explicitly mentioned. The data used for
estimation is shown in Tables S-10 and S-11.
This information was used to estimate the energy required for conversion of cyclohexa2,5-diene-1,4-dicarboxylate to TPA based on weight ratios, and to estimated the required
materials based on stoichiometry, resulting in the inputs and outputs shown in Table S-12.
S -10
Table S-10. Para-xylene, at plant/RNA (from U.S. LCI for production of 1 kg of paraxylene from xylene)
Input
Xylene
Electricity, at grid, US
Natural gas, combusted in industrial boiler/US
Liquefied petroleum gas, combusted in industrial boiler/US
Bituminous coal, combusted in industrial boiler/US
1.00 kg
0.1301 kWh
0.1526 m3
7.594 x 10-3 L
2.57 x 10-2 kg
Output
Para-xylene
1.00 kg
S -11
Table S-11. Purified terephthalic acid, at plant/RER with US electricity U (from Ecoinvent
for production of 1 kg of PTA from xylene)
Input
Water, cooling, unspecified natural origin/m3
Xylene
Water, completely softened, at plant/RER with US electricity
Acetic acid, 98% in H2O, at plant/RER with US electricity
Sodium hydroxide, 50% in H2O, production mix, at plant/RER with US
electricity
Nitrogen, liquid, at plant/RER with US electricity
Electricity, medium voltage, production UCTE, at grid/UCTE with US
electricity
Heat, heavy fuel oil, at industrial furnace 1MW/RER with US electricity
Heat, light fuel oil, at industrial furnace 1MW/RER with US electricity
Heat, natural gas, at industrial furnace >200kW/RER with US electricity
Heat, at hard coal industrial furnace 1-10MW/RER with US electricity
Steam, for chemical processes, at plant/RER with US electricity
Output
Heat, waste
Particulates, > 10 um
Particulates, > 2.5 um, and < 10 um
Particulates, , 2.5 um
Hydrocarbons, aromatic
NMVOC, non-methane volatile organic compounds, unspecified origin
BOD5, Biological oxygen demand
COD, Chemical oxygen demand
DOC, Dissolved organic carbon
TOC, Total organic carbon
Suspended solids, unspecified
Hydrocarbons, unspecified
Disposal, hazardous waste, 0% water, to underground deposit/DE
Disposal, average incineration residue, 0% water, to residual material
landfill/CH with US electricity
Purified terephthalic acid
S -12
3.42 x 10-4 m3
0.661 kg
0.425 kg
0.050 kg
1.45 x 10-3 kg
4.88 x 10-2 kg
0.469 kWh
0.637 MJ
0.212 MJ
0.458 MJ
0.323 MJ
0.64 kg
1.69 MJ
2.88 x 10-5 kg
3.87 x 10-5 kg
2.25 x 10-5 kg
3.78 x 10-4 kg
1.10 x 10-4 kg
1.30 x 10-3 kg
1.30 x 10-3 kg
1.22 x 10-5 kg
1.22 x 10-5 kg
2.56 x 10-4 kg
1.40 x 10-5 kg
2.00 x 10-4 kg
6.00 x 10-3 kg
1 kg
Table S-12. Input/Output data for the production of 1 kg PTA from cyclohexa-2,5-diene1,4-dicarboxylate
Input
Water, cooling, unspecified natural origin/m3
Cyclohexa-2,5-diene-1,4-dicarboxylate
Water, completely softened, at plant/RER with US electricity
Acetic acid, 98% in H2O, at plant/RER with US electricity
Oxygen
Sodium hydroxide, 50% in H2O, production mix, at plant/RER with US
electricity
Nitrogen, liquid, at plant/RER with US electricity
Electricity, medium voltage, production UCTE, at grid/UCTE with US
electricity
Heat, heavy fuel oil, at industrial furnace 1MW/RER with US electricity
Heat, light fuel oil, at industrial furnace 1MW/RER with US electricity
Heat, natural gas, at industrial furnace >200kW/RER with US electricity
Heat, at hard coal industrial furnace 1-10MW/RER with US electricity
Steam, for chemical processes, at plant/RER with US electricity
Electricity, at grid, US
Natural gas, combusted in industrial boiler/US
Liquefied petroleum gas, combusted in industrial boiler/US
Bituminous coal, combusted in industrial boiler/US
Output
Heat, waste
Particulates, > 10 um
Particulates, > 2.5 um, and < 10 um
Particulates, , 2.5 um
Hydrocarbons, aromatic
NMVOC, non-methane volatile organic compounds, unspecified origin
BOD5, Biological oxygen demand
COD, Chemical oxygen demand
DOC, Dissolved organic carbon
TOC, Total organic carbon
Suspended solids, unspecified
Hydrocarbons, unspecified
Disposal, hazardous waste, 0% water, to underground deposit/DE
Disposal, average incineration residue, 0% water, to residual material
landfill/CH with US electricity
Purified terephthalic acid
S -13
3.42 x 10-4 m3
1.012 kg
0.425 kg
0.050 kg
0.096 kg
1.45 x 10-3 kg
4.88 x 10-2 kg
0.469 kWh
0.637 MJ
0.212 MJ
0.458 MJ
0.323 MJ
0.64 kg
-0.08598 kWh
-0.1009 m3
-5.02 x 10-3 L
-0.01699 kg
1.69 MJ
2.88 x 10-5 kg
3.87 x 10-5 kg
2.25 x 10-5 kg
3.78 x 10-4 kg
1.10 x 10-4 kg
1.30 x 10-3 kg
1.30 x 10-3 kg
1.22 x 10-5 kg
1.22 x 10-5 kg
2.56 x 10-4 kg
1.40 x 10-5 kg
2.00 x 10-4 kg
6.00 x 10-3 kg
1 kg
D- PTA 2 Synthesis through Isobutanol Pathway
PTA 2- Synthesis Step 1. Isobutanol production
The benchmark process for production of bio-based isobutanol was the corn to ethanol
process as described in MEG step 1, in Table S-2. The stoichiometry of this reaction is as
follows.
𝐶6 𝐻12 𝑂6
→ 2 𝐶2 𝐻5 𝑂𝐻 (𝑒𝑡ℎ𝑎𝑛𝑜𝑙) + 2 𝐶𝑂2
The weight of CO2 generated in this reaction was calculated as 957 g (= 1000 g ÷ 46 g/mol × 44
g/mol). Since Table S-2 shows the emission of 2526 g biogenic CO2, it seems 1569 g of CO2 is
the extra contribution from the production system (= 2526 g - 957 g). The weight of glucose
consumed in this reaction was calculated as 1957 g (= 1000 g ÷ 46 g/mol × 180 g/mol × 0.5), so
the conversion loss from corn to glucose was estimated as 1.65 (= 3226 g ÷ 1957 g).
The target process stoichiometry is
𝐶6 𝐻12 𝑂6
→
𝐶4 𝐻10 𝑂 (𝑖𝑠𝑜𝑏𝑢𝑡𝑎𝑛𝑜𝑙) + 2𝐶𝑂2 + 𝐻2 𝑂
The weight of CO2 generated in this reaction was calculated as 1189 g (= 1000 g ÷ 74 g/mol ×
44 g/mol × 2). Since the operational contribution of CO2 must be included, 2758 g CO2 was
calculated as the total amount generated in this case (= 1189 g + 1569 g). The weight of glucose
required for this reaction was calculated as 2432 g (= 1000 g ÷ 74 g/mol × 180 g/mol); applying
the conversion loss resulted in a total amount of corn required of 4013 g (2432 g × 1.65). For the
other LCI data, the ratios between the corn mass and the LCI data from the ethanol production
model were applied, resulting in the values shown in Table S-13.
S -14
Table S-13. Input/output flows for 1 kg of bio-isobutanol
Input
Corn, at farm/US with US electricity
Tap water, at user/CH with US electricity
Sulphuric acid, liquid, at plant/RER with US electricity
Soda, powder, at plant
Ammonium sulphate, as N, at regional storehouse
Diammonium phosphate, as N, at regional storehouse
Heat, natural gas, at industrial furnace > 1000kW
Electricity, medium voltage, at grid/US
4.013 kg
5.255 kg
0.030 kg
0.045 kg
0.012 kg
0.012 kg
5.766 MJ
0.178 kWh
Output
Carbon dioxide, biogenic
Heat, waste
Treatment, sewage, from residence, to wastewater treatment, class
Bio-isobutanol
2.758 kg
4.211 MJ
0.002 m3
1 kg
PTA 2- Synthesis Step 2. Isobutylene Production
Isobutanol is then converted to isobutylene by dehydration. Since LCI data are not available, the
dehydration of bio-ethanol to bio-ethylene reported by Liptow et al (2009) for the production of
polyethylene from sugarcane was used as the benchmark. Table S-14 shows the input and output
data for the production of 1 kg of bio-ethylene from bio-ethanol.
Table S-14. Input/output flows for the production of 1 kg of bio-ethylene from bio-ethanol
Input
Bio-ethanol
Electricity
Fuel
1.70 kg
1.80 MJ
5.60 MJ
Output
Methane
Carbon monoxide
Carbon dioxide
Nitrous oxide
NMVOC
NOx
Sulfur dioxide
Bio-ethylene
1.50 x 10-3 kg
2.0 x 10-4 kg
0.327 kg
1.2 x 10-5 kg
1.1 x 10-5 kg
1.5 x 10-3 kg
1.0 x 10-4 kg
1 kg
S -15
For the production of isobutylene, the stoichiometry is
𝐶4 𝐻10 𝑂 (𝑖𝑠𝑜𝑏𝑢𝑡𝑎𝑛𝑜𝑙)
→ 𝐶4 𝐻8 (𝑖𝑠𝑜𝑏𝑢𝑡𝑦𝑙𝑒𝑛𝑒) + 𝐻2 𝑂
The weight of C4H10O required to generate 1 kg of isobutylene is 1.321 kg (= 1.0 kg ÷ 56 g/mol
× 74 g/mol). Scaling the data in Table S-14 using stoichiometry for materials and relative
weights for energy and emissions resulted in the input/output flows for 1 kg of isobutylene
shown in Table S-15.
Table S-15. Input/output flows for the production of 1 kg of bio-isobutylene from bioisobutanol
Input
Bio-isobutanol
Electricity, medium voltage, at grid/US
Heat, natural gas, at industrial furnace > 100 kW
1.32 kg
1.80 MJ
5.60 MJ
Output
Methane
Carbon monoxide
Carbon dioxide
Nitrous oxide
NMVOC
NOx
Sulfur dioxide
Bio-isobutylene
1.50 x 10-3 kg
2.0 x 10-4 kg
0.327 kg
1.2 x 10-5 kg
1.1 x 10-5 kg
1.5 x 10-3 kg
1.0 x 10-4 kg
1 kg
PTA 2- Synthesis Step 3. Isooctene Production
LCI data were also not available for conversion of isobutylene to isooctene. The benchmark
process used for estimation was conversion of the product of refinery MTBE units to isooctane
through dimerization and hydrogenation of C4 components (CDTECH, 2004). Table S-16 shows
the input and output data.
Table S-16 Input/Output flows for the production of isooctene from C4 component.
Input
C4 compounds (isobutene 15 wt%)
100,000 lb
Oxygen
22 lb
Water
40 lb
Output
Isooctene
C4 raffinate
16,680 lb
83,380 lb
S -16
Operational energy requirements were based on a study by Croezen and Kampman (2009),
which reported that steam consumption of 2 tonnes/tonne isooctene is required based on
contractor data, and the process emits 0.3 tonne CO2-eq/tonne isooctene.
From the data presented, it appears that conversion from isobutene to isooctene resulted
in close to 100% yield. Starting material of 100% isobutylene was used as the input material in
this model, and was assumed to have the same 100% process efficiency. Table S-17 presents the
input and output flows for conversion of isobutylene to isooctene.
Table S-17. Input/output flows for 1 kg of isooctene
Input
Steam, for chemical processes, at plant/RER with US electricity
Oxygen, liquid, at plant/RER with US electricity
Isobutylene
Water
2.0 kg
1.319 x 10-3 kg
1.00 kg
2.398 x 10-3 kg
Output
Carbon dioxide
Isooctene
0.333 kg
1.00 kg
PTA 2- Synthesis Step 4. Isooctane Production
Isooctene is then converted into isooctane by hydrogenation. The following equation shows the
stoichiometry of this process.
𝐶8 𝐻16 +
𝐻2
→
𝐶8 𝐻18 (𝑖𝑠𝑜𝑜𝑐𝑡𝑎𝑛𝑒)
Data for this process also were not available in databases, so hydrogenation of 1-heptene
to n-heptane was used as the benchmark (Energetics, Inc., 2006). Table S-18 shows the energy
data reported for this process.
Table S-18 Energy for production of 1 barrel (bbl) of n-heptane
Energy Source
Fuel
Electricity
Total energy input
Hydrogen consumed
Steam (produced)
Amount (BTU)
62,000
19,000
81,000
30,000
-31,100
S -17
The “hydrogen consumed” energy was excluded since it is accounted for separately. Energy
produced by steam was assumed to be recovered and used, so was subtracted from the fuel
energy amount. The stoichiometry of the benchmark process is
𝐶7 𝐻14 ( 1 − ℎ𝑒𝑝𝑡𝑒𝑛𝑒) + 𝐻2
→
𝐶7 𝐻16 (𝑛 − ℎ𝑒𝑝𝑡𝑎𝑛𝑒)
One barrel is 159 L; the density of 1-heptene used was 0.697 g/cm3. Table S-19 shows the inputs
and outputs used for production of n-octene, scaling energy to mass and materials to the
stoichiometry. Natural gas was substituted for “fuel.”
Table S-19. Input/output flows for production of 1 kg isooctane
Input
Electricity, medium voltage, at grid/US
Natural gas, at consumer/RNA with US electricity
Isooctene
Hydrogen, liquid, at plant/RER with US electricity
0.0483 kWh
0.283 MJ
0.982 kg
0.018 kg
Output
Isooctane
1.00 kg
PTA 2- Synthesis Step 5. Para-Xylene Production
Isooctane is then converted into para-xylene by dehydrocyclization. The following equation
shows the stoichiometry of this process.
𝐶8 𝐻18
→ 𝐶8 𝐻10 (𝑝𝑎𝑟𝑎 − 𝑥𝑦𝑙𝑒𝑛𝑒)
+
4𝐻2
As LCI data were not available, the benchmark process used for estimation was
dehydrocyclization for the production of toluene from n-heptane. Table S-20 shows the energy
data for this process, as described by Energetics Inc., 2006.
Table S-20 Toluene production energy data, per barrel
Energy Source
Fuel
Electricity
Total energy input
Hydrogen consumed
Steam (produced)
Amount (BTU)
254,000
10,000
264,000
-479,200
-15,400
S -18
As in the previous step, the “hydrogen consumed” energy was excluded in the study since it was
accounted for separately. The benchmark process stoichiometry is
𝐶7 𝐻16 (𝑛 − ℎ𝑒𝑝𝑡𝑒𝑛𝑒)
→
𝐶7 𝐻8 (𝑡𝑜𝑙𝑢𝑒𝑛𝑒)
+ 4𝐻2
The target process stoichiometry was
𝐶8 𝐻18
→
𝐶8 𝐻10
+ 4𝐻2
Table S-21 shows the input/output flows based on relative amounts and stoichiometry (density of
n-heptene is 0.684 g/cm3). As in step 4, it was assumed that the steam energy was recovered and
used, so it was subtracted from the fuel energy. Natural gas replaced fuel.
Table S-21. Input/ Output flows for 1 kg of para-xylene
Input
Electricity, medium voltage, at grid/US
Natural gas, at consumer/RNA with US electricity
Isooctane
0.0293 kWh
2.516 MJ
1.0755 kg
Output
Hydrogen
Para-xylene
0.0755 kg
1.00 kg
PTA 2- Synthesis Step 6. PTA Production
This process is the same as PTA 1 synthesis step 3, discussed earlier in this document.
E- PTA 3 Synthesis through Benzene Toluene Xylene Pathway
PTA 3- Synthesis Step 1, through Fast Pyrolysis.
The first step in this scenario was production of bio-oil from poplar through fast pyrolysis in a
CFB reactor as described by Iribarrena et al. (2012). Table S-22 shows the demands and
emissions data reported for the production of bio-oil.
S -19
Table S-22. Bio-oil production data
Input
Poplar
Process water
Air
Electricity
Natural gas
5407 kg
89.64 kg
5141 kg
702.4 kWh
1.58 MJ
Output
Bio-oil
Char
Ash
Oxygen
Nitrogen
Water
Hydrogen
Carbon monoxide
Carbon dioxide
Methane
Ethylene
Propylene
Ammonia
2265 kg
86.75 kg
31.21 kg
365 kg
4028 kg
2690 kg
0.03 kg
7.68 kg
1286 kg
2.99 x 10-6 kg
5.98 x 10-6 kg
8.96 x 10-6 kg
4.48 x 10-6 kg
The bio-oil was assumed to be directly converted into BTX through the process of catalytic
(zeolite) upgrading (Huber et al. 2006) with a conversion ratio of 0.83. This resulted in the data
shown in Table S-23.
S -20
Table S-23. Input/Output flows for 1 kg of BTX
Input
Poplar (chips)
Process water, ion exchange, production mix, at plant, from surface
water RER
Air
Electricity, at grid, US
Heat, natural gas, at industrial furnace > 100kW/RER with US
electricity
Output
Charcoal, at plant/GLO with US electricity
Ash, bagasse, at fermentation plant/BR with US electricity
Oxygen
Nitrogen
Water
Hydrogen
Carbon monoxide
Carbon dioxide
Methane
Ethylene
Propylene
Ammonia
BTX
2.876 kg
0.04767 kg
2.734 kg
0.3735 kWh
8.403 x 10-4 MJ
0.04614 kg
0.166 kg
0.1941 kg
2.142 kg
1.431 kg
1.595 x 10-5 kg
4.084 x 10-3 kg
0.684 kg
1.59 x 10-9 kg
3.18 x 10-9 kg
4.765 x 10-9 kg
2.383 x 10-9 kg
1.00 kg
PTA 3 - Synthesis Step 2. Xylene Mix Production
Extractive distillation is used for conversion of BTX to a xylene mix, via the sulfolane process,
used to recover high-purity aromatics from hydrocarbon mixtures, with data from Meyers
(2003). This process consumes an average 287.5 kcal (1.1932 MJ) of energy per kilogram. The
xylene mix weight composition of 33.0% in BTX under the highest yield conditions (upgrading
temperature of 550 ºC) and 100 % extraction were assumed, resulting in the flows shown in
Table S-24, where electricity was substituted for the required energy.
Table S-24 Input/output flows for 1 kg of xylene mixture
Input
Electricity, medium voltage, at grid/US with US electricity
BTX
1.193 MJ
3.030 kg
Output
Xylene mix
1.00 kg
S -21
PTA 3 - Synthesis Step 3. PTA Production
The xylene mixture is then converted into para-xylene by an adsorption, separation and
isomerization process, and para-xylene is converted into PTA by oxidation and purification. LCI
data from Ecoinvent (Purified terephthalic acid, at plant/RER with US electricity U) was used,
resulting in the flows shown in Table S-25.
S -22
Table S-25. Input/output flows for production of 1 kg PTA from xylene mixture
Input
Water, cooling, unspecified natural origin/m3
Xylene mixture
Water, completely softened, at plant/RER with US electricity
Acetic acid, 98% in H2O, at plant/RER with US electricity
Oxygen
Sodium hydroxide, 50% in H2O, production mix, at plant/RER with US
electricity
Nitrogen, liquid, at plant/RER with US electricity
Electricity, medium voltage, production UCTE, at grid/UCTE with US
electricity
Heat, heavy fuel oil, at industrial furnace 1MW/RER with US electricity
Heat, light fuel oil, at industrial furnace 1MW/RER with US electricity
Heat, natural gas, at industrial furnace >200kW/RER with US electricity
Heat, at hard coal industrial furnace 1-10MW/RER with US electricity
Steam, for chemical processes, at plant/RER with US electricity
Electricity, at grid, US
Natural gas, combusted in industrial boiler/US
Liquefied petroleum gas, combusted in industrial boiler/US
Bituminous coal, combusted in industrial boiler/US
Output
Heat, waste
Particulates, > 10 um
Particulates, > 2.5 um, and < 10 um
Particulates, , 2.5 um
Hydrocarbons, aromatic
NMVOC, non-methane volatile organic compounds, unspecified origin
BOD5, Biological oxygen demand
COD, Chemical oxygen demand
DOC, Dissolved organic carbon
TOC, Total organic carbon
Suspended solids, unspecified
Hydrocarbons, unspecified
Disposal, hazardous waste, 0% water, to underground deposit/DE
Disposal, average incineration residue, 0% water, to residual material
landfill/CH with US electricity
Purified terephthalic acid
S -23
3.42 x 10-4 m3
0.661 kg
0.425 kg
0.050 kg
0.096 kg
1.45 x 10-3 kg
4.88 x 10-2 kg
0.469 kWh
0.637 MJ
0.212 MJ
0.458 MJ
0.323 MJ
0.64 kg
-0.08598 kWh
-0.1009 m3
-5.02 x 10-3 L
-0.01699 kg
1.69 MJ
2.88 x 10-5 kg
3.87 x 10-5 kg
2.25 x 10-5 kg
3.78 x 10-4 kg
1.10 x 10-4 kg
1.30 x 10-3 kg
1.30 x 10-3 kg
1.22 x 10-5 kg
1.22 x 10-5 kg
2.56 x 10-4 kg
1.40 x 10-5 kg
2.00 x 10-4 kg
6.00 x 10-3 kg
1 kg
F- Polyethylene Terephthalate Resin Production
Polyethylene terephthalate (PET) resin is obtained through the condensation polymerization
process between MEG and PTA. The PET resin is initially in an almost amorphous state, and its
viscosity is not appropriate for bottle grade resin. Therefore, the amorphous resin goes through
additional polymerization in the solid state in order to increase its viscosity. Tables S-26 and S27 show the inputs and outputs for these processes, for production of 1 kg PET resin. The
Ecoinvent inventory data sources used are “polyethylene terephthalate, granulate, amorphous, at
plant/kg/RER” (from Ecoinvent), which covers condensation polymerization in the liquid state,
and “polyethylene terephthalate, granulate, bottle grade, at plant/kg/RER” for the solid state
polymerization to bottle grade PET resin.
S -24
Table S-26. Input/output flows for production of 1 kg amorphous PET
Input
Water, unspecified natural origin/m3
Water, cooling, unspecified natural origin/m3
Purified terephthalic acid
Mono-ethylene glycol
Nitrogen, liquid, at plant/RER with US electricity
Electricity, medium voltage, production UCTE, at grid/UCTE with US
electricity
Heat, heavy fuel oil, at industrial furnace 1MW/RER with US electricity
Heat, light fuel oil, at industrial furnace 1MW/RER with US electricity
Heat, natural gas, at industrial furnace >200kW/RER with US electricity
Heat, at hard coal industrial furnace 1-10MW/RER with US electricity
Steam, for chemical processes, at plant/RER with US electricity
Output
Heat, waste
Particulates, > 10 um
Particulates, > 2.5 um, and < 10 um
Particulates, , 2.5 um
NMVOC, non-methane volatile organic compounds, unspecified origin
BOD5, Biological oxygen demand
COD, Chemical oxygen demand
DOC, Dissolved organic carbon
TOC, Total organic carbon
Suspended solids, unspecified
Hydrocarbons, unspecified
Disposal, hazardous waste, 0% water, to underground deposit/DE with
US electricity U
Disposal, average incineration residue, 0% water, to residual material
landfill/CH with US electricity
Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH
with US electricity
Disposal, municipal solid waste, 22.9% water, to municipal
incineration/CH with US electricity
Amorphous PET
S -25
1.63 x 10-4 m3
6.40 x 10-3 m3
0.875 kg
0.334 kg
0.0298 kg
0.194 kWh
0.494 MJ
0.165 MJ
0.665 MJ
0.306 MJ
0.94 kg
0.70 MJ
3.20 x 10-7 kg
4.30 x 10-7 kg
2.50 x 10-7 kg
9.00 x 10-4 kg
1.60 x 10-3 kg
1.02 x 10-3 kg
2.62 x 10-4 kg
2.62 x 10-4 kg
1.00 x 10-6 kg
4.99 x 10-4 kg
9.00 x 10-5 kg
4.00 x 10-4 kg
2.31 x 10-3 kg
8.8 x 10-4 kg
1 kg
Table S-27 Input/output flows for production of 1 kg of bottle-grade PET resin
Input
Water, unspecified natural origin/m3
Water, cooling, unspecified natural origin/m3
PET, amorphous
PTA
Mono-ethylene glycol
Nitrogen, liquid, at plant/RER with US electricity
Electricity, medium voltage, production UCTE, at grid/UCTE with US
electricity
Heat, heavy fuel oil, at industrial furnace 1MW/RER with US electricity
Heat, light fuel oil, at industrial furnace 1MW/RER with US electricity
Heat, natural gas, at industrial furnace >200kW/RER with US electricity
Heat, at hard coal industrial furnace 1-10MW/RER with US electricity
Steam, for chemical processes, at plant/RER with US electricity
Output
Heat, waste
Particulates, > 10 um
Particulates, > 2.5 um, and < 10 um
Particulates, , 2.5 um
NMVOC, non-methane volatile organic compounds, unspecified origin
BOD5, Biological oxygen demand
COD, Chemical oxygen demand
DOC, Dissolved organic carbon
TOC, Total organic carbon
Suspended solids, unspecified
Hydrocarbons, unspecified
Disposal, hazardous waste, 0% water, to underground deposit/DE with
US electricity U
Disposal, average incineration residue, 0% water, to residual material
landfill/CH with US electricity
Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH
with US electricity
Disposal, municipal solid waste, 22.9% water, to municipal
incineration/CH with US electricity
Bottle-grade PET
S -26
1.43 x 10-5 m3
4.84 x 10-3 m3
0.78 kg
0.194 kg
0.0761 kg
0.0366 kg
0.189 kWh
0.284 MJ
0.0946 MJ
0.379 MJ
0.172 MJ
0.100 kg
0.68 MJ
3.20 x 10-7 kg
4.30 x 10-7 kg
2.50 x 10-7 kg
1.00 x 10-6 kg
6.31 x 10-4 kg
6.31 x 10-4 kg
6.41 x 10-7 kg
6.41 x 10-7 kg
9.00 x 10-6 kg
1.00 x 10-6 kg
4.30 x 10-4 kg
1.81 x 10-3 kg
6.30 x 10-4 kg
4.00 x 10-54 kg
1 kg
G- Sensitivity Analysis for Energy Input
Process Energy Demand
Since this study contains a number of estimations, a sensitivity check on energy data uncertainty
was performed. We tentatively assumed if there was over a 10% total output change (total
sensitivity %) in the case of a 20% input energy change in a particular step, that step would be
identified as highly sensitive. Sensitivity (%) was expressed as the absolute deviation (%) of the
results.
Table S-28 shows the results for 1 kg of PET bottle grade resin made with the muconic
acid pathway. Input energy amounts were reduced 20% for each PTA production step. Although
significant change (larger than 10 %) was not observed, the PTA 1 step 1 process (muconic acid
synthesis) appeared to have the greatest sensitivity in this study since its sensitivity value of
6.8% was the highest among the three PTA production scenarios. More accurate LCI data should
be procured for this step in a future study.
Table S-28 Results of the sensitivity analysis for uncertainty of PTA scenario 1: Effects of
10% reduction in energy required in each PTA step
Step with 10% reduction
PTA step 1
PTA step 2
PTA step 3
Overall reduction in process energy
6.8%
1.7%
2.0%
Table S-29 shows the reduction in energy in the production of PET bottle grade resin
resulting from a 20% reduction in energy for each step in the isobutanol process for PTA.
Significant change (over 10 %) was not observed.
Table S-30 shows the results for 1 kg PET bottle grade resin made with the BTX pathway
to PTA. No significant change (over 10 %) was observed.
S -27
Table S-29 Results of the sensitivity analysis for uncertainty of PTA scenario 2: Effects of
10% reduction in energy required in each PTA step
Step with 10% reduction
PTA step 1
PTA step 2
PTA step 3
PTA step 4
PTA step 5
PTA step 6
Overall reduction in process energy
3.4%
1.9%
0.8%
0.1%
0.2%
2.3%
Table S-30 Results of the sensitivity analysis for uncertainty of PTA scenario 3: Effects of
10% reduction in energy required in each PTA step
Step with 10% reduction
PTA step 1
PTA step 2
PTA step 3
Overall reduction in process energy
1.2%
1.0%
4.3%
H- Completeness Check
ISO14044 requires that LCA results be checked for completeness. The completeness check is the
process of verifying whether information from the phases of a LCA is sufficient for reaching
conclusions in accordance with the goal and scope definition. As discussed, some processes were
omitted from this study: transportation, processing, use, and end of life. Completeness of the
material production and energy requirements were verified. For PTA 2 step 3, energy required
was assumed to be the same as in the benchmark process. In PTA 3 step 2 for material
production, the conversion efficiency was assumed to be the same as in the petrochemical case.
I- Consistency Check
LCA results must also be checked for consistency. Tables S-31, S-32 and S-33 show the results
of the consistency check. As can be seen in the tables, some processes are not consistent, but
these steps were the targets of this report, so no corrective action was needed.
S -28
In the data accuracy entry, “caution” means that some of the LCI data were based on
stoichiometric estimation. In the technology coverage entry, “commercial” means technology
used in the specific process is already available at an industrial level. “Pilot” means the
technology is not yet available at a mass production level.
Table S-31. Results of consistency check for PTA scenario 1
Data source
MEG
PTA1
Step 1
Step 2
Step 3
PET resin
Comparison
Database,
literature
Literature
Data
accuracy
Good
Caution
Database,
literature
Database,
literature
Database
Caution
Not
consistent
Not
consistent
Good
Good
Data age
Within 6
yrs
Within 6
yrs
Within 6
yrs
Within 6
yrs
Within 6
yrs
Consistent
Technology
coverage
Commercial
Geographical
coverage
US
Pilot
(estimation)
Pilot
(estimation)
Pilot
(estimation)
Commercial
US
Not
consistent
Consistent
Technology
coverage
Commercial
Geographical
coverage
US
Pilot
(estimation)
Pilot
(estimation)
Pilot
(estimation)
Pilot
(estimation)
Pilot
(estimation)
Commercial
US
Commercial
US
Not
consistent
Consistent
US
US
US
Table S-32. Results of consistency check for PTA scenario 2
Data source
MEG
PTA2
PET resin
Comparison
Data
accuracy
Good
Step 1
Database,
literature
Literature
Step 2
Literature
Caution
Step 3
Literature
Caution
Step 4
Literature
Caution
Step 5
Literature
Caution
Step 6
Database,
literature
Database
Good
Not
consistent
Not
consistent
Caution
Good
S -29
Data age
Within 6
yrs
Within 10
yrs
Within 10
yrs
Within 10
yrs
Within 10
yrs
Within 10
yrs
Within 10
yrs
Within 6
yrs
Consistent
US
US
US
US
US
Table S-33. Results of consistency check for PTA scenario 3
Data source
MEG
PTA3
Step 1
Step 2
Database,
literature
Literature
Data
accuracy
Good
Caution
Database,
literature
Database
Caution
PET resin
Database
Good
Comparison
Not
consistent
Not
consistent
Step 3
Good
Data age
Within 6
yrs
Within 6
yrs
Within 6
yrs
Within 6
yrs
Within 6
yrs
Consistent
Technology
coverage
Commercial
Geographical
coverage
US
Pilot
(estimation)
Pilot
(estimation)
Commercial
US
Commercial
US
Not
consistent
Consistent
US
US
J- Uncertainty Analysis - Pedigree Matrix
Table S-34 shows the basic pedigree matrix for this study, with temporal information modified to
this study time. The table provides data quality scores and provides an objective analysis of the
quality of each production step as discussed by Weidema and Wesnæs (1996). Table S-34 shows
the summarized pedigree matrix, indicating the data quality values determined for each step. The
standard deviation (SD) values in Table S-35 were calculated using the following equation as
implemented in SimaPro (SimaPro 7, 2010):
2
2
2
2
2
2
SD = exp√[ln(U1 ) ] + [ln(U2 ) ] + [ln(U3 ) ] + [ln(U4 ) ] + [ln(U5 ) ] + [ln(U6 ) ]
U1 = score for reliability.
U2 = score for completeness.
U3 = score for temporal correlation.
U4 = score for geographical correlation.
U5 = score for technological correlation.
U6 = score for sample size.
S -30
Table S-34. Pedigree matrix with the scores used to assess the quality of data sources (modified from Weidema and
Wesnæs, 1996)
Score
U1 Reliability
U2
Completeness
U3 Temporal
correlation
U4 Geographical
correlation
U5 Further
technological
correlation
U6 Sample size
1
Verified data based on
measurements
2
Verified data partly
based on assumptions
OR non-verified data
based on
measurements
1.05
Representative data
from >50% of sites
relevant for market
considered over
adequate period to
even out normal
fluctuations
1.02
2007-2010
1.03
Average data from
larger area including
area under study
3
Non-verified data
partly based on
qualified estimates
4
Qualified estimate;
data derived from
theoretical
information
5
Non-qualified
estimate
1.10
Representative data
from only some
relevant sites (<<50%)
OR >50% of sites but
from shorter periods
1.20
Representative data
from only one
relevant site OR
some sites but from
shorter periods
1.50
Representativeness
unknown or data
from a small
number of sites
AND shorter
periods
1.05
2003-2006
1.10
Data from smaller area
than area under study,
or from similar area
1.10
1998-2002
1.20
-
1.00
Data from enterprises,
processes and
materials under study
(i.e. identical
technology)
1.00
>100, continuous
measurement
1.01
-
1.02
Data from
processes/materials
under study but
different technology
Data from
laboratory scale
processes and same
technology
1.20
Before 1997
1.50
Data from
unknown OR
distinctly different
area
1.10
Data from
laboratory scale
and different
technology
>20
1.50
≥3
2.00
unknown
1.00
1.02
1.20
>10, aggregated data
in environmental
report
1.05
1.10
1.20
1.00
Representative data
from all sites relevant
for market considered
over adequate period
to even out normal
fluctuations
1.00
2011-2013
1.00
Data from area under
study
S -31
Table S-35. Scores used to assess the quality of data sources and further run the uncertainty analysis
U1
U2
U3
U4
U5
U6
PTA 1
Muconic
acid
Step 1
Energy/
3
4
1
Materials
Step 2
Energy
5
4
2
Materials
4
4
2
Step 3
Energy/
*
*
*
Materials
PTA 2
Step 1
Energy/
4
4
1
Butanol
Materials
Step 2
Energy/
4
4
2
Materials
Step 3
Energy
3
3
3
Materials
4
3
3
Step 4
Energy
2
1
3
Materials
4
1
3
Step 5
Energy
2
1
3
Materials
4
1
3
Step 6
Energy/
*
*
*
Materials
PTA 3
Step 1
Energy/
2
3
1
BTX
Materials
Step 2
Energy/
2
3
3
Materials
Step 3
Energy/
*
*
*
Materials
* Data was used from SimaPro containing standard deviation values
S -32
Calculated
SD2
3
3
5
1.063
3
3
3
3
5
5
1.273
1.116
*
*
*
*
3
3
3
1.081
3
3
4
1.090
3
3
1
1
1
1
3
3
3
3
3
3
3
3
1
1
1
1
1.058
1.084
1.046
1.078
1.046
1.078
*
*
*
*
3
3
4
1.049
3
3
3
1.051
*
*
*
*
K- Additional References
ANL (Argonne National Laboratory) (2010) Life-Cycle Assessment of Corn-Based
Butanol as a Potential Transportation Fuel.Available at:
http://www.transportation.anl.gov/pdfs/AF/448.pdf. Access date:1/29/2013
Brehmer B (2008) Chemical biorefinery perspectives - the valorisation of functionalised
chemicals from biomass resources compared to the conventional fossil fuel
production route. Available at: http://edepot.wur.nl/122048. Access date:3/18/2013
Burk M, Osterhout R, Sun J (2011) US Patent 2011/0124911 A1. Semi-synthetic
terephthalic acid via microorganisms that produce muconic acid
CDTECH (2004) Technology profile report, Conversion of Refinery MTBE Units for
Isooctene/Isooctane Production. CDTECH®, 2004. Available at
http://www.cdtech.com/techProfilesPDF/Dimer%208.pdf. Access date: 3/4/2013
Croezen H, Kampman B (2009) The impact of ethanol and ETBE blending on refinery
operations and GHG-emissions. Energ Policy 37(12):5226-5238
Energetics Incorporated (2006) Energy Bandwidth for Petroleum Refining Processes,
Industrial Technologies Programs, U.S. Department of Energy. Available at:
http://www1.eere.energy.gov/manufacturing/resources/petroleum_refining/pdfs/band
width.pdf. Access date: 1/19/2013
Huber G.W, Iborra S, Corma A (2003) Synthesis of Transportation Fuels from Biomass:
Chemistry, Catalysts, and Engineering. Chem Reviews 106:4044-4098
Iribarren D, Peters JF, Dufour J (2012) Life cycle assessment of transportation fuels from
biomass pyrolysis. Fuel 97:812-821
Liptow D, Tillman A (2009) Comparative life cycle assessment of polyethylene based on
sugarcane and crude oil. Chalmers University of Technology. Available at:
http://cpmdatabase.cpm.chalmers.se/DataReferences/ESA_2009--14.pdf. Access
date: 10/13/2012.
Meyers, R (2003) Handbook of Petroleum Refining Processes, 3rd ed, McGraw Hill,
chapter 9
Portha JF, Jaubert JN, Louret S, Pons MN (2010) Life Cycle Assessment Applied to
Naphtha Catalytic Reforming. Oil Gas Sci Technol 65:793-805
S - 33
Office of Energy Efficiency & Renewable Energy (2000) Technical report, “The BTX
Chain: Benzene, Toluene, Xylene”, U.S. Department of Energy. Available at:
http://www1.eere.energy.gov/manufacturing/resources/chemicals/pdfs/profile_chap4
.pdf. Access date: 1/31/2013
SimaPro 7 (2010) Introduction into LCA , Pré International
Van Duuren J, Brehmer B, Mars A, Eggink G, Martins dos Santos V, Sanders J (2011) A
Limited LCA of Bio-Adipic Acid: Manufacturing the Nylon-6,6 Precursor Adipic
Acid Using the Benzoic Acid Degradation Pathway From Different Feedstocks.
Biotech.Bioeng 108:1298–1306
Weidema B, Wesnæs M (1996) Data Quality Management for Life Cycle Inventories –
An Example of Using Data Quality Indicators. J Clean Prod 4:167-174
Zhang Y (2008) Ecologically-Based LCA, An Approach for Quantifying the Role of
Natural Capital in Product Life Cycles. Ph.D. Dissertation, Ohio State University,
Chemical Engineering. Available at:
http://etd.ohiolink.edu/view.cgi?acc_num=osu1222102539. Access date:1/29/2013
S - 34