SUPPORTING INFORMATION
Enthalpy data and toxicity score for all reactants and products
The enthalpies of combustion and formation are determined based on Joback’s group
contribution method [1,2] and the method by Marrero & Gani [2]. The toxicity score TS is
determined based on the classification of R-phrases. The upper bound of the TS is set to 1000
representing the maximal value in the TS classification [3,4].
∆HCombustion [kJ/mol]
∆HFormation [kJ/mol]
TS [-]
Biomass
2800
-770
Cellulose
2800
-770
Hemicellulose
2800
-770
Lignin
2800
-770
Hydrogen
242
0
Oxygen
0
0
Water
0
-242
Carbon monoxide
283
-111
Carbon dioxide
0
-394
Methane
803
-75
300
Ethanol
1277
-237
300
Furan
1998
-62
1000
Butanol
2507
-278
400
2-Methylfuran
2601
-94
750
2-methyltetrahydrofuran
2961
-218
400
3-methyltetrahydrofuran
2961
-218
400
2-5-Dimethylfurane
3205
-126
400
Ethyllevulinate
3591
-618
300*
Butyllevulinate
4821
-659
300*
Tetrahydrofurfurallevulinate
5123
-751
400
1
Tetrahydrofuran
2356
-188
400
Ethylfuran
3247
-84
300
Ethyltetrahydrofuran
3568
-247
400*
2-5-Dimethyltetrahydrofuran
3558
-257
300
Butylfuran
4477
-126
300
Butyltetrahydrofuran
4798
-288
400*
Cyclohexanol
3550
-265
400
Benzylalcohol
3634
-90
400
6-Butylundecane
9421
-358
300*
6-Pentylundecane
10036
-379
300*
ethylfurfurylether
3699
-267
300*
ethyltetrahydrofurfurylether
4059
-392
300
Octanol
4968
-360
300
Acetone
1690
-217
300
Table A1: Enthalpy data and toxicity scores. * The score is based on a molecule with a similar
molecular structure.
2
Environmental impact
The simplified version of the EI calculation relies on energy consumption (EC), resource
consumption (RC), emission impact (Em) and toxicity potential (TP). Equations (A1) to (A4)
show the formulae for the individual factors:
∆
= ∙
= ∙
∙
∑ (A1)
=
(A3)
= !"#$ % !"#$
(A2)
∙
&'
()))
(A4)
Em not only accounts for CO2 emissions, but also for the CO2-equivalent of other gas
emissions with global warming potential. For the determination of the toxicity potential,
components with a high molecular similarity are classified similarly (same toxicity score), when
no risk and safety sentences are available. This avoids a misinterpretation of the toxicity
potential due to a non-existing toxicity classification, which is often the case for newly
developed molecules. As outlined in [3,4], the toxicity score TS is classified into harmless (TS: 0300) and injuring effects (TS > 300). Ethanol has a TS of 0, which causes problems since the
toxicity potential would be omitted due to a resulting weighting factor of 0. Hence all fuel
candidates exhibiting a toxicity score of 0 or 100 are set to TS of 300. Due to the classification
into harmless and injuring effects, this approach does not change the general statement, whether
a molecule is harmless or not.
Standardization of the environmental impact
To avoid a dependency of the normalization on the case study, the four single impacts are
weighted based on the reference production of ethanol (cf. Eq. (3)), which exhibits an EI of 1.
All impacts contribute equally (25%) to the EI in case of ethanol. The normalization is based on
3
the production of 100 000 tons of cellulosic ethanol per year, which is equivalent to a heating
value of 2.77·1012 kJ/year. Equations (A5) to (A8) show the calculation of the weighting factors:
).-.
*+ = +
/0
=
).-.
*2 = 2
/0
).-.∙/0 ∙/0
=
∆/0
).-.∙/0 ∙/0
∙
).-.
(A5)
*1+ = 1+
(A7)
*&3 =
The calculation of the energy loss ∆
67
/0
).-.
&3/0
=
).-.∙/0 ∙/0
∑ =
).-.∙&'45
/0 ∙/0 ∙&'/0
(A6)
(A9)
requires the enthalpy of combustion of all educts
and of the product ethanol; this data is compiled in Table A1. For each mole of ethanol one mole
of CO2 is released during fermentation. With this information the individual factors for ethanol
and the weighting factors can be calculated as follows:
:;
67 [ <= ]
= 20.17
→
67 [−]
= 2.77
→ *1+ = 0.090 [−]
<=GH-IJ.
67 F<=KLMNOPQR
<=KLMNOPQ
67 [
TIUL
= 0.96
] = 0.0299
→
<=
*+ = 0.013 [:;]
<=KLMNOPQ
*2 = 0.261 [ <=GH-IJ. ]
TIUL
XY
→ *&3 = 8.35 ∙ 10 [<=KLMNOPQ]
4
Reaction yields and references
Reaction yields have been collected from literature and are compiled in Table A2. Unknown
reaction yields are marked and set to 0.97. The split of lignin into its constituents is assumed to
be ideal and marked with “Assumption Lignin”. The split between the lignin alcohols is
implemented using optimization constraints. The upper bound of the reaction yields is 1 in case
of chemical conversions representing the theoretical yield. The determination of the theoretical
yield differs for the fermentations. The upper bound in case of ethanol is 0.51 g/g (R8), for
itaconic acid 0.72 g/g (R9), for butanol 0.5 g/g (R10) and in case of succinic acid 1.1 g/g (R50)
respectively.
reaction
yield
reference
reaction
yield
reference
R1
0.97
Assumption
R51
0.94
[5]
R2
0.97
Assumption
R52
0.97
[6]
R3
0.97
Assumption
R53
0.94
[6]
R4
0.54
[7]
R54
1
[6]
R5
0.97
[8]
R55
0.4
[9]
R6
0.97
[10]
R56
0.9
[11]
R7
0.9
[12]
R57
0.51
[13]
R8
0.47*
[14]
R58
0.81
[15]
R9
0.62*
[16]
R59
0.83
[17,18]
R10
0.39*
[19]
R60
0.95
[18]
R11
0.7
[20]
R62
1
[21]
R12
0.7
[20]
R63
0.925
[22]
R13
1
[20]
R64
0.95
[15]
R14
0.99
[23]
R65
1
Assumption Lignin
R15
0.95
[23]
R66
0.97
Assumption
R16
0.99
[23]
R67
0.97
Assumption
R17
1
[23]
R68
0.97
Assumption
R18
1
[23]
R69
0.97
Assumption
R19
1
[23]
R70
0.83
[24]
5
R20
0.96
[23]
R71
1
[25]
R21
1
[23]
R72
1
[26]
R22
1
[23]
R73
0.97
Assumption
R23
0.97
[23]
R74
0.97
Assumption
R24
0.8
[20]
R75
0.9
[27]
R25
0.9
[6]
R76
0.92
[28]
R26
0.97
[6]
R77
0.95
[29]
R27
1
[30]
R78
0.968
[31]
R28
0.8
[32]
R79
1
[33]
R29
0.97
[34]
R80
1
[35]
R30
0.29
[36]
R81
0.95
[37]
R31
0.79
[36]
R82
0.91
[38]
R32
0.99
[39]
R83
1
Assumption Lignin
R33
0.83
[40]
R84
1
Assumption Lignin
R34
1
[41]
R85
0.94
[42]
R35
0.87
[43]
R86
1
[42]
R36
0.66
[44]
R87
0.96
[42]
R37
0.95
[45]
R88
0.86
[42]
R38
0.95
[45]
R89
1
[42]
R39
0.95
[45]
R90
0.973
[42]
R40
0.95
[45]
R91
0.93
[42]
R41
0.94
[45]
R92
1
[42]
R42
0.94
[45]
R93
0.942
[42]
R43
0.67
[45]
R94
0.97
Assumption
R44
0.93
[46]
R95
0.97
Assumption
R45
0.8
[47]
R96
0.63
[48]
R46
0.8
[47]
R97
0.97
Assumption
R47
0.8
[47]
R48
0.8
[47]
R49
0.95
[49]
R50
0.91*
[50]
Table A2: Reaction yields and references for all network reactions. * Fermentation yield given in [g/g]
6
Parameter variation
For the sensitivity analysis all parameters are varied for the determination of their individual
influence. The weighting factors of the EI, the property data and toxicity score as well as the
reaction yields are presented in Tables 1, A1 and A2. In addition, the parameters determining the
cost calculations as well as lower and upper bound of biomass composition are presented in
Table A3.
description
parameter
unit
value
reference
RC_B
Raw material costs biomass
$/kg
0.05
[47]
RC_H2
Raw material costs hydrogen
$/kg
2.7
[20]
RC_H2O
Raw material costs water
$/kg
0.0005
[43]
RC_FA
Raw material costs formic acid
$/kg
1.05
[43]
RC_MeOH Raw material costs methanol
$/kg
1
[43]
RC_A
Raw material costs acetone
$/kg
0.81
[44]
i
Interest rate
%
Assumption
n
Run time
years
8
10
Invest1
Coefficient for IC calculation
-
3
[51]
Invest2
Coefficient for IC calculation
-
0.84
[51]
lb_C
Lower bound cellulose fraction
-
0.4
[20]
ub_C
Upper bound cellulose fraction
-
0.8
[20]
lb_HC
Lower bound hemicellulose fraction
-
0.15
[20]
ub_HC
Upper bound hemicellulose fraction
-
0.3
[20]
lb_lignin
Lower bound lignin fraction
-
0.1
[20]
ub_lignin
Upper bound lignin fraction
-
0.25
[20]
Assumption
Table A3: Additional parameters required in the RNFA
7
Influence of the parameter Invest2 on the sensitivity analysis
The OAT as well as the MC analysis identified the parameter Invest2 as the most influential
parameter. Therefore a detailed discussion and quantification of this parameter’s influence is
conducted in the following. Figure 1 shows the comparison of the results of OAT analysis with
and without considering the parameter Invest2 in the sensitivity analysis. In addition, Table A4
quantifies the maximum relative deviations from the results of the RNFA for nominal parameters
with and without considering the parameter Invest2 for the case of minimal TAC.
OAT incl. all parameter [%]
OAT w/o Invest2 [%]
Ethanol
46
28
2-MF
57
24
2-MTHF
38
33
PUD
45
29
EFE
61
22
EL
42
31
Cyclohexanol
83
Methane
57
17
57
fuel
Table A41: Maximal relative deviations for the point of minimal TAC, with and without considering
Invest2 coefficient
Both, the graphical comparison as well as the quantification of the maximal relative deviations
underline the statement of the high influence of the cost coefficient on the process analysis. But
there exist also distinct differences for the different fuel candidates and their respective
production processes. While the cost coefficient clearly has a high influence for cylohexanol,
there is no influence on the process performance for methane. This might be due to the very low
TAC of the methane process compared to the cyclohexanol process. The most stable behaviour
considering all parameter variations are shown for the fuel candidates 2-MTHF, EL, PUD and
ethanol, which exhibit an uncertainty range of ±46% in the TAC. Without the consideration of
8
the parameter Invest2, for all fuel candidates except methane, the TAC are within a range of
±33% compared to the nominal cases. Hence the high influence of the parameter Invest2 can be
proven by the results of OAT analysis. Figure 2 presents the analogue comparison for the MC
analysis. Both analyses show the strong influence of the cost coefficient Invest2 for each topscorer.
9
1. Results of OAT analysis for top-scorers with and without parameter Invest2
10
Figure 1: Monte Carlo analysis- left: 15 %deviation including all parameters; right 15% deviation excluding
parameter Invest2
11
2. Results of MC analysis for top-scorers with and without parameter Invest2
12
Figure 2: Monte Carlo analysis- left: 15 %deviation including all parameters; right 15% deviation excluding
parameter Invest2
13
Results of Monte Carlo analysis for a parameter variation of ± 30%
Figure 3: Monte Carlo results for a 30% parameter deviation
14
Results of Monte Carlo analysis for a parameter variation of ± 30%
Figure 4: MC results for all top-scorer. Left: Minimization of TAC, Right: Minimization of EI
15
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