Supplemental A Schematic diagram of custom-built steam-treatment device
1
Supplemental B (Part 1) Correlation between solid residues yield (ST and HWE) and
non-modified P-factor. Fitting parameters of solid residues yield data using Eq. (4)
listed in Supplemental B (Part 2) (ST: α = 92.36 ± 2.25,  = -1.2567(E-6) ±
3.1051(E-7), R2 = 0.6422; HWE: α = 95.87 ± 2.71,  = -1.5606(E-6) ± 3.5543(E-7),
R2 = 0.6935).
100
Solid residue yield (%)
Measured data
Fitting line
ST
HWE
90
80
70
60
0
50000
100000
150000
200000
250000
Non-modified P-factor (min)
Supplemental B (Part 2) Reasons for using modified P-factor to describe the intensity
of ST and HWE
The chemical reactions that occur during water-based prehydrolyses (ST and
HWE) typically consist of carbohydrate hydrolysis, along with some delignification
and lignin condensation. Although the reaction system is very complex, if we do not
attempt to understand the mechanism, these macroscopic reactions can normally be
described by pseudo-first-order reaction kinetics (Kobayashi and Sakai 1956). Based
on this kinetic argument and an average activation energy (Ea, 134 kJ/mol) for
delignification of hardwood and softwood in alkali pulping processes, previously, an
H-factor (Eq. (1)) has been used to combine reaction temperature and time into a
2
single variable, to allow comparison and control of processes (Vroom 1957).
Following the research conducted by Brasch and Free (1965), Lin (1979) extended the
H-factor principle to the prehydrolysis process, and developed another control factor
(called the P-factor, Eq. (2)) using an Ea of 125.6 kJ/mol for the cleavage of
glycosidic bonds of carbohydrate in wood (eucalyptus). Later, also based on the above
kinetic considerations, Abatzoglou et al. (1992) formalized the concept of severity
factor (R0, Eq. (3)), originally proposed by Overend and Chornet (1987). It is
reasonable to believe that these three factors essentially similar.
The expressions for the three factors are:
t
 Ea, L
Ea, L
H   Exp

0
 R  373.15 R  Tt

dt

(1)
t
 Ea, H
Ea, H
P   Exp

0
 R  373.15 R  Tt

dt

(2)
t
 T  373.15 
R0   Exp t
dt
0
 14.75 
(3)
where, Ea,L (134 kJ/mol) is the average of the activation energies for hardwood (117
kJ/mol) and softwood (150 kJ/mol) delignification in the alkali pulping process, and
Ea,H (125.6 kJ/mol) is the activation energy for hydrolysis of fast-hydrolyzing xylan
in eucalyptus chips.
These three factors have been regarded as ordinates to describe the prehydrolysis
processes of lignocelluloses. For example, without any modification, mass loss and
hemicellulose removal during ST and HWE correlated well with the H-factor (Yoon et
al., 2008; Liu 2010), R0 (Overend and Chornet 1987; Caparros et al., 2006) and
P-factor (Sixta 2006; Duarte et al., 2011). However, probably because of the different
3
cell wall structures for different lignocellulosic materials, the Ea used in the
traditional factors does not necessarily apply to all raw materials. To improve the
fitting between experimental prehydrolysis results and these process parameters (H-,
P- and severity factor), different Ea values obtained from the kinetics of the
corresponding process have been used to modify both the P-factor and R0 (Borrega et
al., 2013; Garrote et al., 2002; Luo et al., 2013b).
The exponential correction of solid residue yield with P-factor is obtained for
both ST and HWE (Fig.1 (a)). The prediction function was given as
YSolid    Exp(  P)
(4)
where, α can be interpreted as maximum mass loss and  would be a parameter used
to differentiate two prehydrolysis methods (ST and HWE), which probably cause
different cell wall structure of bamboo chips during reaction process.
By using Eq. (4), the fitting correlation coefficients (R2) between the solid
residue yields obtained in this study (Supplemental B (part 1)) and the non-modified
P-factor are < 0.7, indicating the inapplicability of the empirical Ea (125.6 kJ/mol).
Modifying the P-factor by replacing the empirical Ea by an average Ea (46.5 kJ/mol)
for pentosan dissolution from green bamboo during HWE (44.9 kJ/mol, Ma et al.,
2011) and ST (48.1 kJ/mol, Luo et al., 2013b) gave better fitting results (R2 for both
ST and HWE > 0.9). Our previous study (Luo et al., 2013b) also showed that the
empirical Ea used in the equation for R0 should be modified to achieve satisfactory
fitting results for the relationship between pentosan removal and R0 during ST of
green bamboo. For this reason, the intensities of ST and HWE have been described by
4
a modified P-factor in this study.
Cited References
Abatzoglou N, Chornet E, Belkacemi K, and Overend RP (1992) Phenomenological kinetics of complex
systems: the development of a generalized severity parameter and its application to
lignocellulosics fractionation. Chem Eng Sci 47(5): 1109-1122
Borrega M, Tolonen LK, Bardot F, Testova L, Sixta H (2013) Potential of hot water extraction of birch
wood to produce high-purity dissolving pulp after alkaline pulping. Bioresour Technol 135:
665–671
Brasch DJ, Free KW (1965) Prehydrolysis-kraft pulping of Pinus radiata grown in New Zealand. TAPPI
48(4): 245-248
Caparrós S, Garrote G, Ariza J, and López F (2006) Autohydrolysis of Arundo donax L., a kinetic
assessment. Ind Eng Chem Res 45(26): 8909-8920
Duarte GV, Ramarao BV, Amidon TE, Ferreira PT (2011) Effect of hot water extraction on hardwood
kraft pulp fibers (Acer saccharum, sugar maple). Ind Eng Chem Res 50(17): 9949-9959
Garrote G, Domı ́nguez H, Parajó JC (2002) Interpretation of deacetylation and hemicellulose hydrolysis
during hydrothermal treatments on the basis of the severity factor. Proc Biochem 37(10),
1067-1073.
Kobayash T, Sakai Y (1956) Hydrolysis rate of pentosan of hardwood in dilute sulfuric acid. Bull Agric
Chem Soc Jpn 20(1): 1-7
Lin CK (1979) Prehydrolysis-alkaline pulping of sweetgum wood. Department of Wood and Paper
Science. North Carolina State University: Raleigh, NC, USA
Liu S (2010) Woody biomass: Niche position as a source of sustainable renewable chemicals and
energy and kinetics of hot-water extraction/hydrolysis. Biotechnol Adv 28(5): 563-582
Luo XL, Ma XJ, Hu HC, Li CH, Cao SL, Huang LL, Chen LH (2013) Kinetic study of pentosan solubility
during heating and reacting processes of steam treatment of green bamboo. Bioresour Technol
130: 769–776
Ma XJ, Huang LL, Chen YX, Chen LH (2011) Preparation of bamboo dissolving pulp for textile
production; Part 1. Study on prehydrolysis of green bamboo for producing dissolving pulp.
BioResources 6(2): 1428–1439
Overend RP, Chornet E, Gascoigne JA (1987) Fractionation of lignocellulosics by steam-aqueous
pretreatments [and discussion]. Phil Trans R Soc Lond A 321(1561): 523–536
Sixta H (2006) Handbook of Pulp, Wiley-VCH, Weinheim, pp 325–365 and 1009–1067
Yoon SH, Macewan K, Van Heiningen ARP (2008) Hot-water pre-extraction from loblolly pine (Pinus
taeda) in an integrated forest products biorefinery. Tappi J 7(6): 27-32
Vroom KE (1957) The “H” factor: a means of expressing cooking times and temperatures as a single
variable. Pulp Paper Mag Can 58(3): 228-231
5
Supplemental C Effect of active chlorine charge on dioxide chlorine bleaching
performance
D1
D2
Active
chlorine
charge (%)
pulp
yield
(%)
Pentosan
content
(%)
Alpha-cellulose
content (%)
Ash
content
(%)
Kappa
number
Brightness
(% ISO)
Cellulose
viscosity
(mL/g)
1.14
1.52
1.90
2.28
0.20
0.40
31.0
30.6
30.3
29.6
26.8
26.6
2.38
2.20
1.84
1.81
1.40
1.33
96.93
97.25
97.55
97.62
97.29
97.89
0.32
0.28
0.23
0.19
0.16
0.15
3.0
2.2
1.9
1.3
1.0
1.2
56.1
66.2
73.2
78.5
86.8
88.2
977
949
927
879
794
759
0.60
0.80
1.00
26.2
25.9
25.7
1.31
1.31
1.29
97.84
98.11
98.18
0.17
0.15
0.16
1.1
1.2
0.9
88.5
88.3
88.6
680
630
632
6