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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

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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.

Similarity1. Chemical reaction process Same Almost the same Slightly different Different

2. Output material Same Almost the same Slightly different Different

3. Input material Same Almost the same Slightly 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 H 5 OH →C2 H 4(ethylene)+H 2 O , ∆ H f =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

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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 H 12O6 → 2C2 H 5 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.

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Table S-2. Input/output flows for 1 kg of bio-ethanolInputCorn, at farm/US with US electricity 3.226 kgTap water, at user/CH with US electricity 4.224 kgSulphuric acid, liquid, at plant/RER with US electricity 0.024 kgSoda, powder, at plant 0.036 kgAmmonium sulphate, as N, at regional storehouse 0.010 kgDiammonium phosphate, as N, at regional storehouse 0.010 kgHeat, natural gas, at industrial furnace > 1000kW 4.635 MJElectricity, medium voltage, at grid/US 0.143 kWh

OutputCarbon dioxide, biogenic 2.526 kgHeat, waste 3.385 MJTreatment, sewage, from residence, to wastewater treatment, class 0.001 m3

Bio-ethanol 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..

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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 H 5 OH →C2 H 4(ethylene)+H 2 O

Obtained ethylene is then converted into ethylene oxide by oxidation.

2 C2 H 4+O2→ 2 C2 H 4 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

InputOxygen, liquid, at plant/RER with US electricity 0.463 kgElectricity, medium voltage, production UCTE at grid/UCTE with US electricity 0.33 kWhBio-ethanol 0.825 kg

OutputCarbon dioxide, fossil 0.21 kgCarbon monoxide, fossil 1.1 x 10-4 kgEthene (ethylene) 2.3 x 10-4 kgEthylene oxide 2.0 x 10-5 kgHeat, waste 1.2 MJMethane, fossil 7.5 x 10-5 kgNMVOC, non-methane volatile organic compounds, unspecified origin 2.4 x 10-4 kgBOD5, Biological oxygen demand 1.9 x 10-4 kgCOD, Chemical oxygen demand 1.9 x 10-4 kgDOC, Dissolved organic carbon 2.0 x 10-4 kgTOC, Total organic carbon 2.0 x 10-4 kgDisposal, catalyst base Eth. Oxide prod., 0% water, to residual material landfill/CH with US electricity

5.0 x 10-4 kg

Bio-ethylene oxide 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.

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C2 H 4 O+2 H 2O →2 C2 H 6 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-MEGInputWater, cooling, unspecified natural origin/m3 0.024 m3

Bio-ethylene oxide 0.05146 kgBio-ethanol 0.538 kgHeat, natural gas, at industrial furnace >100 kW/RER 2.0 MJElectricity, medium voltage, production UCTE, at grid/UCTE with US electricity 0.333 kWh

OutputHeat, waste 1.199 MJEthylene oxide 2.619 x 10-3 kgEthanol 2.739 x 10-3 kgCarbon dioxide, fossil 9.245 x 10-2 kgBOD5, Biological oxygen demand 9.16 x 10-3 kgCOD, Chemical oxygen demand 9.16 x 10-3 kgDOC, Dissolved organic carbon 2.86 x 10-3 kgTOC, Total organic carbon 2.86 x 10-3 kgBio-MEG 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 H 12O 4 ( mucconicacid )+CO2

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

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Demand/emissions CED, GJ CO2, kg N2O, kgPhenol (lignin) feedstock, wheat stover 7.710 9.550 2.660Bioreactor (fermentation) 0.240 0.010 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, US-

EI 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.

Table S-6. Feed demands for bacterial growth in the bioreactor, for production of 1000 kg

of adipic acidFeedstock AmountAmmonium sulphate 0.070 tonPotassium phosphate 0.090 tonGlucose 0.440 tonSodium hydroxide 0.560 tonHydrochloric acid 0.540 ton

Adipic acid is made by hydrogenation of muconic acid:

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C6 H 6 O4(muconic acid)+2 H 2→ C6 H 10O 4(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 acidInputElectricity, medium voltage, production UCTE, at grid/UCTE with US electricity 5.794 MJGasoline, combusted in industrial equipment/US 0.030 LDiesel, combusted in equipment/US 0.144 LHydrogen 0.028 kgAmmonium sulphate 0.07202 kgSodium phosphate 0.051 kgSodium hydroxide 0.576 kgHydrochloric acid 0.556 kg

OutputCarbon dioxide 0.723 kgNitrous oxide 0.013 kgMuconic acid 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

temperature for 12 hours. An initial pressure of 3.5 MPa is applied. The following equation

shows the stoichiometry of this process.

C6 H 6 O4+C2 H 2 →C8 H 8O4 (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.

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Table S-8. Cyclohexane production dataInputBenzene 0.93 kgHydrogen 0.078 kgSteam 0.1 kgElectricity 0.041 kWhCatalyst 6.2 x 10-5 kg

OutputBenzene 4.7 x 10-4 kgHydrogen 1.5 x 10-6 kgCatalyst 6.2 x 10-5 kgCyclohexane 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-1,4-

dicarboxylate 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 cyclohexa-

2,5-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.

Table S-9. Input/Output flows for 1 kg of cyclohexa-2,5-diene-1,4-dicarboxylateInputElectricity, medium voltage, production UCTE, at grid/UCTE with US electricity 0.041 kWhSteam, for chemical processes, at plant/RER with US electricity 0.10 kgMuconic acid 0.845 kgAcetylene, at regional storehouse/CH with US electricity 0.155 kg

OutputMuconic acid 4.27 x 10-4 kgAcetylene, at regional storehouse/CH with US electricity 2.981 x 10-6 kgCyclohexa-2,5-diene-1,4-dicarboxylate 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,

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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.

2 C8 H 8 O4+O2→ 2C8 H 6O 4(TPA )+2 H 2 OSince 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 cyclohexa-

2,5-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.

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Table S-10. Para-xylene, at plant/RNA (from U.S. LCI for production of 1 kg of para-

xylene from xylene)InputXylene 1.00 kgElectricity, at grid, US 0.1301 kWhNatural gas, combusted in industrial boiler/US 0.1526 m3

Liquefied petroleum gas, combusted in industrial boiler/US 7.594 x 10-3 LBituminous coal, combusted in industrial boiler/US 2.57 x 10-2 kg

OutputPara-xylene 1.00 kg

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Table S-11. Purified terephthalic acid, at plant/RER with US electricity U (from Ecoinvent

for production of 1 kg of PTA from xylene)InputWater, cooling, unspecified natural origin/m3 3.42 x 10-4 m3

Xylene 0.661 kgWater, completely softened, at plant/RER with US electricity 0.425 kgAcetic acid, 98% in H2O, at plant/RER with US electricity 0.050 kgSodium hydroxide, 50% in H2O, production mix, at plant/RER with US electricity 1.45 x 10-3 kgNitrogen, liquid, at plant/RER with US electricity 4.88 x 10-2 kgElectricity, medium voltage, production UCTE, at grid/UCTE with US electricity 0.469 kWhHeat, heavy fuel oil, at industrial furnace 1MW/RER with US electricity 0.637 MJHeat, light fuel oil, at industrial furnace 1MW/RER with US electricity 0.212 MJHeat, natural gas, at industrial furnace >200kW/RER with US electricity 0.458 MJHeat, at hard coal industrial furnace 1-10MW/RER with US electricity 0.323 MJSteam, for chemical processes, at plant/RER with US electricity 0.64 kg

OutputHeat, waste 1.69 MJParticulates, > 10 um 2.88 x 10-5 kgParticulates, > 2.5 um, and < 10 um 3.87 x 10-5 kgParticulates, , 2.5 um 2.25 x 10-5 kgHydrocarbons, aromatic 3.78 x 10-4 kgNMVOC, non-methane volatile organic compounds, unspecified origin 1.10 x 10-4 kgBOD5, Biological oxygen demand 1.30 x 10-3 kgCOD, Chemical oxygen demand 1.30 x 10-3 kgDOC, Dissolved organic carbon 1.22 x 10-5 kgTOC, Total organic carbon 1.22 x 10-5 kgSuspended solids, unspecified 2.56 x 10-4 kgHydrocarbons, unspecified 1.40 x 10-5 kgDisposal, hazardous waste, 0% water, to underground deposit/DE 2.00 x 10-4 kgDisposal, average incineration residue, 0% water, to residual material landfill/CH with US electricity

6.00 x 10-3 kg

Purified terephthalic acid 1 kg

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Table S-12. Input/Output data for the production of 1 kg PTA from cyclohexa-2,5-diene-

1,4-dicarboxylateInputWater, cooling, unspecified natural origin/m3 3.42 x 10-4 m3

Cyclohexa-2,5-diene-1,4-dicarboxylate 1.012 kgWater, completely softened, at plant/RER with US electricity 0.425 kgAcetic acid, 98% in H2O, at plant/RER with US electricity 0.050 kgOxygen 0.096 kgSodium hydroxide, 50% in H2O, production mix, at plant/RER with US electricity 1.45 x 10-3 kgNitrogen, liquid, at plant/RER with US electricity 4.88 x 10-2 kgElectricity, medium voltage, production UCTE, at grid/UCTE with US electricity 0.469 kWhHeat, heavy fuel oil, at industrial furnace 1MW/RER with US electricity 0.637 MJHeat, light fuel oil, at industrial furnace 1MW/RER with US electricity 0.212 MJHeat, natural gas, at industrial furnace >200kW/RER with US electricity 0.458 MJHeat, at hard coal industrial furnace 1-10MW/RER with US electricity 0.323 MJSteam, for chemical processes, at plant/RER with US electricity 0.64 kgElectricity, at grid, US -0.08598 kWhNatural gas, combusted in industrial boiler/US -0.1009 m3

Liquefied petroleum gas, combusted in industrial boiler/US -5.02 x 10-3 LBituminous coal, combusted in industrial boiler/US -0.01699 kg


6.00 x 10-3 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.

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C6 H12O6 → 2C2 H5 OH (ethanol )+2CO2

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 )+2 C O2+H 2O

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.

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Table S-13. Input/output flows for 1 kg of bio-isobutanolInputCorn, at farm/US with US electricity 4.013 kgTap water, at user/CH with US electricity 5.255 kgSulphuric acid, liquid, at plant/RER with US electricity 0.030 kgSoda, powder, at plant 0.045 kgAmmonium sulphate, as N, at regional storehouse 0.012 kgDiammonium phosphate, as N, at regional storehouse 0.012 kgHeat, natural gas, at industrial furnace > 1000kW 5.766 MJElectricity, medium voltage, at grid/US 0.178 kWh

OutputCarbon dioxide, biogenic 2.758 kgHeat, waste 4.211 MJTreatment, sewage, from residence, to wastewater treatment, class 0.002 m3

Bio-isobutanol 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-ethanolInputBio-ethanol 1.70 kgElectricity 1.80 MJFuel 5.60 MJ

OutputMethane 1.50 x 10-3 kgCarbon monoxide 2.0 x 10-4 kgCarbon dioxide 0.327 kgNitrous oxide 1.2 x 10-5 kgNMVOC 1.1 x 10-5 kgNOx 1.5 x 10-3 kgSulfur dioxide 1.0 x 10-4 kgBio-ethylene 1 kg

For the production of isobutylene, the stoichiometry is

C4 H 10O(isobutanol)→ C4 H 8(isobutylene)+H 2 O

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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 bio-

isobutanolInputBio-isobutanol 1.32 kgElectricity, medium voltage, at grid/US 1.80 MJHeat, natural gas, at industrial furnace > 100 kW 5.60 MJ

OutputMethane 1.50 x 10-3 kgCarbon monoxide 2.0 x 10-4 kgCarbon dioxide 0.327 kgNitrous oxide 1.2 x 10-5 kgNMVOC 1.1 x 10-5 kgNOx 1.5 x 10-3 kgSulfur dioxide 1.0 x 10-4 kgBio-isobutylene 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.InputC4 compounds (isobutene 15 wt%) 100,000 lbOxygen 22 lbWater 40 lb

OutputIsooctene 16,680 lbC4 raffinate 83,380 lbOperational 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.

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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 isoocteneInputSteam, for chemical processes, at plant/RER with US electricity 2.0 kgOxygen, liquid, at plant/RER with US electricity 1.319 x 10-3 kgIsobutylene 1.00 kgWater 2.398 x 10-3 kg

OutputCarbon dioxide 0.333 kgIsooctene 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 H 16+H 2 →C8 H 18(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-heptaneEnergy Source Amount (BTU)Fuel 62,000Electricity 19,000Total energy input 81,000Hydrogen consumed 30,000Steam (produced) -31,100

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)

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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 isooctaneInputElectricity, medium voltage, at grid/US 0.0483 kWhNatural gas, at consumer/RNA with US electricity 0.283 MJIsooctene 0.982 kgHydrogen, liquid, at plant/RER with US electricity 0.018 kg

OutputIsooctane 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 H 10( para−xylene)+4 H 2

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 barrelEnergy Source Amount (BTU)Fuel 254,000Electricity 10,000Total energy input 264,000Hydrogen consumed -479,200Steam (produced) -15,400As 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 H 16(n−heptene)→ C7 H 8(toluene)+4 H 2

The target process stoichiometry was

C8 H18 →C8 H 10+4 H 2

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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-xyleneInputElectricity, medium voltage, at grid/US 0.0293 kWhNatural gas, at consumer/RNA with US electricity 2.516 MJIsooctane 1.0755 kg

OutputHydrogen 0.0755 kgPara-xylene 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.

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Table S-22. Bio-oil production dataInputPoplar 5407 kgProcess water 89.64 kgAir 5141 kgElectricity 702.4 kWhNatural gas 1.58 MJ

OutputBio-oil 2265 kgChar 86.75 kgAsh 31.21 kgOxygen 365 kgNitrogen 4028 kgWater 2690 kgHydrogen 0.03 kgCarbon monoxide 7.68 kgCarbon dioxide 1286 kgMethane 2.99 x 10-6 kgEthylene 5.98 x 10-6 kgPropylene 8.96 x 10-6 kgAmmonia 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 BTXInputPoplar (chips) 2.876 kgProcess water, ion exchange, production mix, at plant, from surface water RER 0.04767 kgAir 2.734 kgElectricity, at grid, US 0.3735 kWhHeat, natural gas, at industrial furnace > 100kW/RER with US electricity 8.403 x 10-4 MJ

OutputCharcoal, at plant/GLO with US electricity 0.04614 kgAsh, bagasse, at fermentation plant/BR with US electricity 0.166 kgOxygen 0.1941 kgNitrogen 2.142 kgWater 1.431 kgHydrogen 1.595 x 10-5 kgCarbon monoxide 4.084 x 10-3 kgCarbon dioxide 0.684 kgMethane 1.59 x 10-9 kgEthylene 3.18 x 10-9 kgPropylene 4.765 x 10-9 kgAmmonia 2.383 x 10-9 kgBTX 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 mixtureInputElectricity, medium voltage, at grid/US with US electricity 1.193 MJBTX 3.030 kg

OutputXylene mix 1.00 kgPTA 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

S - 21

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 mixtureInputWater, cooling, unspecified natural origin/m3 3.42 x 10-4 m3

Xylene mixture 0.661 kgWater, completely softened, at plant/RER with US electricity 0.425 kgAcetic acid, 98% in H2O, at plant/RER with US electricity 0.050 kgOxygen 0.096 kgSodium hydroxide, 50% in H2O, production mix, at plant/RER with US electricity 1.45 x 10-3 kgNitrogen, liquid, at plant/RER with US electricity 4.88 x 10-2 kgElectricity, medium voltage, production UCTE, at grid/UCTE with US electricity 0.469 kWhHeat, heavy fuel oil, at industrial furnace 1MW/RER with US electricity 0.637 MJHeat, light fuel oil, at industrial furnace 1MW/RER with US electricity 0.212 MJHeat, natural gas, at industrial furnace >200kW/RER with US electricity 0.458 MJHeat, at hard coal industrial furnace 1-10MW/RER with US electricity 0.323 MJSteam, for chemical processes, at plant/RER with US electricity 0.64 kgElectricity, at grid, US -0.08598 kWhNatural gas, combusted in industrial boiler/US -0.1009 m3

Liquefied petroleum gas, combusted in industrial boiler/US -5.02 x 10-3 LBituminous coal, combusted in industrial boiler/US -0.01699 kg


6.00 x 10-3 kg


S - 23

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 S-

27 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 PETInputWater, unspecified natural origin/m3 1.63 x 10-4 m3

Water, cooling, unspecified natural origin/m3 6.40 x 10-3 m3

Purified terephthalic acid 0.875 kgMono-ethylene glycol 0.334 kgNitrogen, liquid, at plant/RER with US electricity 0.0298 kgElectricity, medium voltage, production UCTE, at grid/UCTE with US electricity 0.194 kWhHeat, heavy fuel oil, at industrial furnace 1MW/RER with US electricity 0.494 MJHeat, light fuel oil, at industrial furnace 1MW/RER with US electricity 0.165 MJHeat, natural gas, at industrial furnace >200kW/RER with US electricity 0.665 MJHeat, at hard coal industrial furnace 1-10MW/RER with US electricity 0.306 MJSteam, for chemical processes, at plant/RER with US electricity 0.94 kg

OutputHeat, waste 0.70 MJParticulates, > 10 um 3.20 x 10-7 kgParticulates, > 2.5 um, and < 10 um 4.30 x 10-7 kgParticulates, , 2.5 um 2.50 x 10-7 kgNMVOC, non-methane volatile organic compounds, unspecified origin 9.00 x 10-4 kgBOD5, Biological oxygen demand 1.60 x 10-3 kgCOD, Chemical oxygen demand 1.02 x 10-3 kgDOC, Dissolved organic carbon 2.62 x 10-4 kgTOC, Total organic carbon 2.62 x 10-4 kgSuspended solids, unspecified 1.00 x 10-6 kgHydrocarbons, unspecified 4.99 x 10-4 kgDisposal, hazardous waste, 0% water, to underground deposit/DE with US electricity U

9.00 x 10-5 kg

Disposal, average incineration residue, 0% water, to residual material landfill/CH with US electricity

4.00 x 10-4 kg

Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH with US electricity

2.31 x 10-3 kg

Disposal, municipal solid waste, 22.9% water, to municipal incineration/CH with US electricity

8.8 x 10-4 kg

Amorphous PET 1 kg

S - 25

Table S-27 Input/output flows for production of 1 kg of bottle-grade PET resinInputWater, unspecified natural origin/m3 1.43 x 10-5 m3

Water, cooling, unspecified natural origin/m3 4.84 x 10-3 m3

PET, amorphous 0.78 kgPTA 0.194 kgMono-ethylene glycol 0.0761 kgNitrogen, liquid, at plant/RER with US electricity 0.0366 kgElectricity, medium voltage, production UCTE, at grid/UCTE with US electricity 0.189 kWhHeat, heavy fuel oil, at industrial furnace 1MW/RER with US electricity 0.284 MJHeat, light fuel oil, at industrial furnace 1MW/RER with US electricity 0.0946 MJHeat, natural gas, at industrial furnace >200kW/RER with US electricity 0.379 MJHeat, at hard coal industrial furnace 1-10MW/RER with US electricity 0.172 MJSteam, for chemical processes, at plant/RER with US electricity 0.100 kg

OutputHeat, waste 0.68 MJParticulates, > 10 um 3.20 x 10-7 kgParticulates, > 2.5 um, and < 10 um 4.30 x 10-7 kgParticulates, , 2.5 um 2.50 x 10-7 kgNMVOC, non-methane volatile organic compounds, unspecified origin 1.00 x 10-6 kgBOD5, Biological oxygen demand 6.31 x 10-4 kgCOD, Chemical oxygen demand 6.31 x 10-4 kgDOC, Dissolved organic carbon 6.41 x 10-7 kgTOC, Total organic carbon 6.41 x 10-7 kgSuspended solids, unspecified 9.00 x 10-6 kgHydrocarbons, unspecified 1.00 x 10-6 kgDisposal, hazardous waste, 0% water, to underground deposit/DE with US electricity U

4.30 x 10-4 kg

Disposal, average incineration residue, 0% water, to residual material landfill/CH with US electricity

1.81 x 10-3 kg

Disposal, plastics, mixture, 15.3% water, to municipal incineration/CH with US electricity

6.30 x 10-4 kg

Disposal, municipal solid waste, 22.9% water, to municipal incineration/CH with US electricity

4.00 x 10-54 kg

Bottle-grade PET 1 kg

S - 26

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 stepStep with 10% reduction Overall reduction in process energyPTA step 1 6.8%PTA step 2 1.7%PTA step 3 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


10% reduction in energy required in each PTA stepStep with 10% reduction Overall reduction in process energyPTA step 1 3.4%PTA step 2 1.9%PTA step 3 0.8%PTA step 4 0.1%PTA step 5 0.2%PTA step 6 2.3%


10% reduction in energy required in each PTA stepStep with 10% reduction Overall reduction in process energyPTA step 1 1.2%PTA step 2 1.0%PTA step 3 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.

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

S - 28

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 1Data source Data accuracy Data age Technology

coverageGeographical coverage

MEG Database, literature

Good Within 6 yrs Commercial US

PTA1 Step 1 Literature Caution Within 6 yrs Pilot (estimation)

US

Step 2 Database, literature

Caution Within 6 yrs Pilot (estimation)

US


Good Within 6 yrs Pilot (estimation)

US

PET resin Database Good Within 6 yrs Commercial USComparison Not consistent Not consistent Consistent Not consistent Consistent





PTA2 Step 1 Literature Caution Within 10 yrs

Pilot (estimation)

US

Step 2 Literature Caution Within 10 yrs

Pilot (estimation)

US


Pilot (estimation)

US


Pilot (estimation)

US


Pilot (estimation)

US


Good Within 10 yrs

Commercial US

PET resin Database Good Within 6 yrs Commercial USComparison Not consistent Not consistent Consistent Not consistent Consistent





PTA3 Step 1 Literature Caution Within 6 yrs Pilot (estimation)

US


Caution Within 6 yrs Pilot (estimation)

US

Step 3 Database Good Within 6 yrs Commercial USPET resin Database Good Within 6 yrs Commercial USComparison Not consistent Not consistent Consistent Not consistent Consistent

S - 29

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):

SD = exp√ [ ln ( U1 )2 ]+ [ ln (U2 )2 ] + [ln (U3 )2 ]+ [ ln ( U4 )2 ]+ [ ln ( U5 )2 ]+ [ ln (U6 )2 ]

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 1 2 3 4 5U1 Reliability Verified data based on

measurementsVerified data partly based on assumptions OR non-verified data based on measurements

Non-verified data partly based on qualified estimates

Qualified estimate; data derived from theoretical information

Non-qualified estimate

1.00 1.05 1.10 1.20 1.50U2 Completeness

Representative data from all sites relevant for market considered over adequate period to even out normal fluctuations

Representative data from >50% of sites relevant for market considered over adequate period to even out normal fluctuations

Representative data from only some relevant sites (<<50%) OR >50% of sites but from shorter periods

Representative data from only one relevant site OR some sites but from shorter periods

Representativeness unknown or data from a small number of sites AND shorter periods

1.00 1.02 1.05 1.10 1.20U3 Temporal correlation

2011-2013 2007-2010 2003-2006 1998-2002 Before 19971.00 1.03 1.10 1.20 1.50

U4 Geographical correlation

Data from area under study

Average data from larger area including area under study

Data from smaller area than area under study, or from similar area

- Data from unknown OR distinctly different area

1.00 1.01 1.02 1.10U5 Further technological correlation

Data from enterprises, processes and materials under study (i.e. identical technology)

- Data from processes/materials under study but different technology

Data from laboratory scale processes and same technology

Data from laboratory scale and different technology

1.00 - 1.20 1.50 2.00U6 Sample size >100, continuous

measurement>20 >10, aggregated data

in environmental report

≥ 3 unknown

1.00 1.02 1.05 1.10 1.20

S - 31

Table S-35. Scores used to assess the quality of data sources and further run the uncertainty analysisU1 U2 U3 U4 U5 U6 Calculated

SD2

PTA 1 Muconic acid

Step 1 Energy/ Materials 3 4 1 3 3 5 1.063

Step 2 Energy 5 4 2 3 3 5 1.273Materials 4 4 2 3 3 5 1.116

Step 3 Energy/ Materials * * * * * * *

PTA 2 Butanol







PTA 3 BTX Step 1 Energy/ Materials 2 3 1 3 3 4 1.049



* Data was used from SimaPro containing standard deviation values

S - 32

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/

bandwidth.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

http://cpmdatabase.cpm.chalmers.se/DataReferences/ESA_2009--14.pdf

http://www1.eere.energy.gov/manufacturing/resources/petroleum_refining/pdfs/bandwidth.pdf

http://www1.eere.energy.gov/manufacturing/resources/petroleum_refining/pdfs/bandwidth.pdf

http://www.transportation.anl.gov/pdfs/AF/448.pdf

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

http://www1.eere.energy.gov/manufacturing/resources/chemicals/pdfs/profile_chap4.pdf

http://www1.eere.energy.gov/manufacturing/resources/chemicals/pdfs/profile_chap4.pdf

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