Estudio sobre la optimización de un proceso de hidrolización térmica de aguas residuales para el proceso de digestión anaerobia.

1. Bioresource Technology 321 (2021) 124498
Available online 11 December 2020
0960-8524/© 2020 Elsevier Ltd. All rights reserved.
Optimization of thermal hydrolysis process for enhancing anaerobic
digestion in a wastewater treatment plant with existing primary
sludge fermentation
Peijun Zhou a
, Mohamed N.A. Meshref a,b
, Bipro Ranjan Dhar a,*
a
Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta T6G 1H9, Canada
b
Public Works Department, Faculty of Engineering, Ain Shams University, 1 El Sarayat St., Abbassia, Cairo 11517, Egypt
H I G H L I G H T S G R A P H I C A L A B S T R A C T
• THP was assessed for wastewater treat­
ment plant with primary sludge
fermentation.
• Two process schemes studied under
various severity index ranged from 2.4
to 4.1.
• Temperature had more impact on sludge
solubilization than exposure times.
• THP of TWAS + FPS provided higher
methane yield than THP of TWAS alone.
• High severity index values adversely
affected methane yields under both
schemes.
A R T I C L E I N F O
Keywords:
Anaerobic digestion
Thermal hydrolysis process (THP)
Biomethane
Thickened waste activated sludge (TWAS)
Fermented primary sludge (FPS)
A B S T R A C T
Many wastewater treatment plants (WWTPs) adopted primary sludge fermentation to produce sludge liquor for
the biological denitrification process. The fermented primary sludge (FPS) is usually co-digested with thickened
waste activated sludge (TWAS) in the anaerobic digestion (AD) process. To date, there has been limited infor­
mation on how the sludge thermal hydrolysis process (THP) could be retrofitted for enhancing AD in WWTPs
with the existing primary sludge fermentation process. This study assessed two THP retrofitting schemes, (FPS +
TWAS and TWAS alone) combining different exposure times (15, 30, and 60 min) and temperatures (140, 160,
and 180 ◦
C). The results suggested that temperature had more impact on sludge solubilization than exposure
times. Notably, 180 ◦
C was the most effective for sludge solubilization under both schemes. However, a higher
degree of solubilization did not necessarily lead to higher methane yields. The THP of FPS + TWAS attained
considerably higher methane yield than the pretreatment of TWAS alone.
1. Introduction
Sludge management and disposal can range in cost from 20% up to
60% of the total operational cost of a wastewater treatment plant
(WWTP) (Grubel et al., 2014). Anaerobic digestion (AD) is widely
accepted approach for sludge solubilization, sludge volume reduction,
* Corresponding author.
E-mail address: bipro@ualberta.ca (B.R. Dhar).
Contents lists available at ScienceDirect
Bioresource Technology
journal homepage: www.elsevier.com/locate/biortech
https://doi.org/10.1016/j.biortech.2020.124498
Received 15 October 2020; Received in revised form 27 November 2020; Accepted 28 November 2020

2. Bioresource Technology 321 (2021) 124498
2
and biogas production in centralized wastewater treatment plants (Ali
and Sun, 2019; Kor-Bicakci and Eskicioglu, 2019). Unfortunately, the
AD process has some challenges due to the rate-limiting hydrolysis step;
therefore, various pretreatment methods have been extensively
researched and applied to improve process kinetics (Kim et al., 2003).
To date, various sludge pretreatment methods, such as mechanical
(ultrasonic, microwave, electrokinetic, and high-pressure homogeniza­
tion), thermal, chemical (acidic, alkali, ozonation, Fenton, Fe(II)-
activated persulfate oxidation, etc.), and biological options (tempera­
ture-phased anaerobic digestion and microbial electrolysis cell) have
been investigated for improving anaerobic biodegradability of sewage
sludge (Nazimudheen et al., 2018; Takashima and Tanaka, 2014; Zhen
et al., 2017). Among different pretreatment technologies, thermal hy­
drolysis process (THP) has been the most extensively investigated (Ali
and Sun, 2019) and commercially implemented in full-scale (Barber,
2016; Zhen et al., 2017).
THP was originally used to enhance sludge dewaterability (Zhen
et al., 2017). Subsequently, it was proven to be a successful approach to
improve the solubilization of sludge and reduce viscosity of sludge
(Bougrier et al., 2006; Higgins et al., 2017; Liu et al., 2019), as well as
enhance biogas production (Neyens and Baeyens, 2003). Therefore, due
to those proven benefits, various commercial thermal hydrolysis pro­
cesses, such as Cambi® Thermal Hydrolysis Process (Cambi AS) and
BioThelys® (Veolia Waters Technologies) have been demonstrated in
the pilot- and full-scale (Bougrier et al., 2008; Kor-Bicakci and Eskicio­
glu, 2019). To date, there are over 75 facilities worldwide operating or
planning THP prior to the AD process (Barber, 2016).
The performance of THP heavily relies on treatment temperature and
retention/exposure time (Zhen et al., 2017). According to the literature,
the temperature of THP is typically conducted in the ranges of
60–180 ◦
C, while the treatment time varies typically from 15 min to 60
min (Bougrier et al., 2008; Carrère et al., 2008; Dwyer et al., 2008; Kepp
et al., 2000). Although THP has been commercially employed for over
20 years, there remain numerous opportunities for the further evolution
of this technology. For instance, the destruction of volatile solids during
anaerobic digestion of sludge remains relatively modest (60–65%), even
with THP (Barber, 2016). Moreover, THP is reported to be more effec­
tive for the solubilization of carbohydrates and proteins rather than
lipids (Barber, 2016). The primary sludge usually contains more lipids
(Wilson and Novak, 2009). Nonetheless, THP has been mostly imple­
mented in the lab- and full-scale for solubilization of a mixture of pri­
mary sludge and waste activated sludge (Barber, 2016). Interestingly,
the use of primary sludge fermentation has drawn considerable attention
recently by many centralized WWTPs, which provides a breakdown of
unsaturated fats to volatile fatty acids (VFAs) that can be utilized as an
exogenous carbon source for the biological nutrient removal process
(Barua et al., 2019; Zheng et al., 2010). Given that more stringent reg­
ulations for nutrients removal, this would lead many WWTPs to adopt
primary sludge fermentation to complement the biological nutrient
removal process. It is expected that the feed sludge characteristics for
anaerobic digestion would be quite different in WWTPs with primary
sludge fermentation as compared to WWTPs without sludge fermenta­
tion. Thus, it remains an open question whether either a mixture of
fermented primary sludge (FPS) and thickened waste activated sludge
(TWAS) or TWAS alone should be implemented for THP in WWTPs with
sludge fermentation.
To close this gap, the present study focused on the optimization and
enhancement of THP process conditions for wastewater treatment plants
with primary sludge fermentation. The main objective of this study was
to investigate the impacts of the THP process schemes and operating
conditions for improving anaerobic co-digestion of FPS and TWAS. The
specific objectives were as follows: (i) to assess and optimize the relative
efficacy of the THP process conditions (temperature and exposure time,
or pretreatment severity index); (ii) to systematically evaluate and grasp
the differences between two process schemes (FPS + TWAS and TWAS
alone) targeting enhancement of sludge solubilization and biomethane
recovery via retrofitting THP in WWTPs with primary sludge fermen­
tation. Based on the authors’ knowledge, the results of this study present
the first experimental investigation to the appraisal of THP for WWTPs
with primary sludge fermentation.
2. Materials and methods
2.1. Sludge and inoculum
For this study, FPS, TWAS, and anaerobic digester sludge were
collected from the Gold Bar Wastewater Treatment Plant; WWTP
(Edmonton, Alberta, Canada). At the Gold Bar WWTP, primary sludge
undergoes an anaerobic fermentation process. The liquid effluent (also
called sludge liquor) from the fermentation process is used as a carbon
source in biological nutrient removal in the secondary treatment pro­
cess. The FPS is mixed with TWAS at a volume ratio of 1:1 and used as a
feedstock for anaerobic digesters operated at 37 ◦
C. The anaerobic
digester sludge was used as the inoculum for this study. The full-scale
anaerobic digestion facility at the Gold Bar WWTP is operated at
37 ◦
C and fed with a mixture of FPS and TWAS. The samples were stored
at 4 ◦
C in the cold room before use. Table 1 summarizes the character­
istics of FPS, TWAS, and digested sludge.
2.2. Thermal treatment experiments
The thermal hydrolysis of sludge was carried out using a 2 L bench-
scale hydrothermal reactor (Parr 4848, Max. temperature: 350 ◦
C, Max.
pressure: 1900 psi, Parr Instrument Company, Moline, IL, USA). The
hydrothermal reactor was equipped with an automated controller with
auto-tuning capabilities that allows for accurate monitoring of both the
heating and cooling parameters including target temperature, holding
time (soak) as well as the heating/cooling rate (Lin et al., 2019). The
reactor content was continuously mixed at 150 rpm with the aid of a
mechanical mixer connected to a speed controller (Lin et al., 2019). For
each test condition, 450 mL of sludge was loaded into the reactor vessel.
After sealing the vessel, the mechanical mixer was set and kept running
until the end of the cooling cycle. The heating rate was 2–3 ◦
C/min
before reaching 100 ◦
C. Afterward, the heating rate was 0.5–1 ◦
C/min.
After reaching the desired temperature, the temperature was maintained
for the preferred exposure time (15/30/60 min). Then, the reactor was
cooled down to room temperature by circulating cold water. In most
cases, the entire cooling process took ~3 h to lower the temperature
below 50 ◦
C.
Two experimental schemes were investigated for THP prior to the
AD; a schematic representation of different experimental schemes is
provided in the Supporting materials. In scheme-1, thermal hydrolysis
Table 1
Characteristics of substrate and inoculum.
Parameters Inoculum Substrate
Digested
sludge
FPS* TWAS** FPS +
TWAS***
TSS (mg/L) 22,444 ±
694
58,222 ±
7,074
49,778 ±
2,912
54,000 ±
4,868
VSS (mg/L) 19,333 ±
1,453
51,444 ±
5,501
42,889 ±
509
47,167 ±
3005
TCOD (mg/L) 25,375 ±
1,431
68,189 ±
4,185
47,716 ±
1,277
57,953 ± 19
SCOD (mg/L) 2,744 ±
1,049
8,542 ± 881 1,682 ± 511 5,112 ± 185
TVFA (mg
COD/L)
42 ± 42 3,411 ± 79 160 ± 48 1786 ± 28
TAN (mg/L) 1,122 ± 11 121 ± 10 45 ± 12 83 ± 11
pH 7.0 ± 0 4.8 ± 0 6.2 ± 0 5.5 ± 0
*Fermented primary sludge (FPS).
**Thickened waste activated sludge (TWAS).
*** Mixture of FPS and TWAS (volume ratio of 1:1).
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3. Bioresource Technology 321 (2021) 124498
3
was conducted for a mixture of FPS and TWAS (volume ratio of 1:1). In
scheme-2, thermal hydrolysis was performed only for TWAS, and then
mixed with FPS (volume ratio of 1:1) prior to AD. For both schemes,
hydrothermal experiments were performed at different temperatures
(140, 160, and 180 ◦
C) and exposure times (15, 30, and 60 min) (see
Table 2). During experiments, depending on the operating temperature,
pressures reached at 40 psi (140 ◦
C), 80 psi (160 ◦
C), and 120–140 psi
(180 ◦
C). Moreover, a mixture of untreated FPS and TWAS (volume ratio
of 1:1) was used for the control test.
The detailed experimental design of the THP with respect to severity
index (SI) is provided in Table 2. Of note, SI is a parameter widely
adopted in THP applications that combines the operating temperature
and retention time into one single parameter (Razavi et al., 2019). In this
study, the experimental design was conducted considering eight
different SI values (2.4, 2.7, 2.9, 3.0, 3.2, 3.5, 3.8, and 4.1). The SI was
calculated via Eq. (1) (Kakar et al., 2019; Hendriks and Zeeman, 2009;
Razavi et al., 2019):
SI = log
⎛
⎝t × e[T− 100
14.75 ]
⎞
⎠ (1)
where T is the pretreatment temperature (◦
C), and t is the pretreatment
retention time (minute).
2.3. Biochemical methane potential (BMP) test
The effectiveness of different pretreatment conditions was assessed
with the biochemical methane potential (BMP) test (Dhar et al., 2012).
The BMP test was performed with a batch anaerobic bioreactor system
(ISES-Canada, Vaughan, ON, Canada). The system consisted of 500 mL
glass anaerobic bioreactors equipped with mechanical stirrers and
electrical motors. The BMP tests were conducted for three different
conditions: control (untreated FPS + untreated TWAS + inoculum),
scheme-1 (treated FPS and TWAS + inoculum), scheme-2 (untreated
FPS + treated TWAS + inoculum), and blank (DI water + inoculum). All
experiments were conducted in triplicate. Based on the total working
volume of 310 mL, the volumes of substrate and inoculum were esti­
mated based on food to microorganism ratio (F/M) of 2 [g of total
chemical oxygen demand (TCOD) of sludge/g of voltaile suspended
solids (VSS) of inoculum]. Before starting the experiment, the reactors
were purged with nitrogen gas for 3 min to create an anaerobic condi­
tion. No trace nutrients were provided in the reactors. However, 5 g/L of
sodium bicarbonate buffer was added to each reactor to avoid any pH
drop during batch operation of BMP tests. The pH values in the reactors
were raneged from 6.65 to 7.1 (initial) and 7.4–7.8 (final). During ex­
periments, mesophilic condition (37 ± 2 ◦
C) was maintained with water
baths. The gas outlet port of each reactor was connected to an absorption
bottle for capturing acidic gases (e.g., CO2, H2S, etc.) from biogas (Ryue
et al., 2019). The absorption solution contained 3 M NaOH with thy­
molphthalein as pH-indicator, which could allow capturing all acidic
gases from the biogas (Ryue et al., 2019). Thus, pure methane gas could
be collected in the gas bags. The volume of methane gas produced from
each reactor was measured on a regular basis with a frictionless glass
syringe. The total duration of the experiment was 25 days.
2.4. Analytical methods
The raw and pretreated samples were analyzed for total chemical
oxygen demand (TCOD), soluble chemical oxygen demand (SCOD), total
suspended solids (TSS), VSS, total ammonia nitrogen (TAN), various
volatile fatty acids (VFAs), and pH. The TSS and VSS concentrations
were determined according to standard methods (APHA, 2012). The
COD and TAN concentrations were measured using Hach reagent kits
(Hach Co., Loveland, Colorado, USA). Samples were filtered with 0.45
μm membrane syringe filters for SCOD and TAN analysis. The VFAs
concentrations were measured with an ion chromatograph (DionexTM
ICS-2100, Thermos Scientific, USA) equipped with an electrochemical
detector (ECD) and microbore AS19, 2 mm column. For analysis of VFAs
(acetate, propionate, and butyrate), samples were filtered with 0.2 μm
membrane syringe filters. pH was measured using a bench-top pH meter
(AR15 pH meter, Fisher Scientific, Pittsburgh, PA). The performance of
the pretreatment process can be determined by the degree of solubili­
zation and the solids removal. The degree of COD solubilization (%) was
calculated using Eq. (2) (Kakar et al., 2020; Kumar Biswal et al., 2020):
Degree of solubilization (%) =
(SCODTHP − SCODraw)
(TCODraw − SCODraw)
× 100 (2)
Where SCODTHP is the concentration of soluble COD of substrate
after THP (mg/L), SCOD raw is the soluble COD concentration of the raw
sample (mg/L), and TCOD raw is the total COD concentration of the raw
sample (mg/L). The VSS removal efficiencies were calculated using Eq.
(3) (Azizi et al., 2019):
VSS removal(%) =
(VSSB − VSSA)
(VSSB)
(3)
where VSSB is the VSS concentration before thermal hydrolysis (mg/L),
and VSSA is the VSS concentration after thermal hydrolysis (mg/L).
2.5. Kinetic modeling
First-order (Eq. (4)) and modified Gompertz (Eq. (5)) kinetic models
were used to evaluate process kinetics from the experimental BMP tests
data (Barua et al., 2018; Li et al., 2015; Liu et al., 2020):
V(t) = Vm(1 − e− kt
) (4)
V(t) = Vm.exp
{
− exp[1 + (λ − t)
Re
Vm
]
}
(5)
where V(t) is the cumulative methane production at time t (mL), Vm is
the maximum methane yield (mL), k is the kinetic (or methanogenesis)
rate constant (d-1
), λ is the lag phase time (days), R is the maximum
methane production rate (mL/day), and e is mathematical constant
(2.718282). The measured experimental values of Vm was used in the
models. The relative least squares method in the Microsoft Excel Solver
was initially implemented to estimate the best-fit values of kinetic pa­
rameters (k, R, and λ). While using the solver, the normalized errors
were adjusted to be minimal ≤ 0.5. Due to the limited iterations in the
Microsoft Excel Solver (5 iterations), further non-linear regression an­
alyses using Minitab 19 software was performed to ensure generating
the best model fit and values. The starting values estimated from Excel
solver was used in the first iteration in Minitab to minimize the standard
error estimate and to attain best fit model of the data. In Minitab ana­
lyses, the Gauss-Newton Algorithm and maximum of 400 iterations was
used and tolerance of 10-5
, and 95% confidence level for all intervals
were preserved. It is noticed that the estimated values k from both Excel
solver and Minitab in most of the experimental data sets were matched
(differences were 2–3%).
Table 2
Hydrothermal pretreatment design of this study.
Temperature (◦
C) Exposure time (minute) Severity Index
140 15 2.4
140 30 2.7
140 60 3.0
160 15 2.9
160 30 3.2
160 60 3.5
180 15 3.5
180 30 3.8
180 60 4.1
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4. Bioresource Technology 321 (2021) 124498
4
2.6. Statistical analysis
To determine that significant differences between the characteristics
of pretreated samples; various statistical analyses in Minitab 19 were
performed such as one-way analysis of variance (ANOVA) to compare
the values of mean of the data sets for any statistical differences in
addition to Tukey Pairwise Comparisons to verify which treatment
conditions were statistically different from each other considering the
important parameters. The significant confidence level was targeted at
95% (P-values < 0.05 were considered significant). Similarly, the
principal component analysis (PCA) was performed to evaluate and
highlight the potential relationships and correlations between the pre­
treatment conditions and the sludge substrates in schemes-1 and 2.
3. Results and discussion
3.1. Impact of pre-treatment on sludge solubilization
3.1.1. COD and suspended solids solubilization
Fig. 1 a-d shows the TCOD and SCOD concentrations of untreated
(control) and pretreated samples from the two experimental schemes. In
scheme-1 (FPS + TWAS), SCOD concentrations significantly increased
from 5112 ± 185 mg/L (untreated FPS + TWAS) to a range of 15065 ±
1021 to 26126 ± 8488 mg/L (p < 0.001). The maximum SCOD con­
centration was observed for the pretreatment at 160 ◦
C, 30 min. Anal­
ogous to scheme-1, SCOD concentration also increased for all
pretreatment conditions under scheme-2 (TWAS only). However, the
maximum increase in SCOD concentration was achieved at 180 ◦
C, 60
min. The fold increases of SCOD in scheme-1 were lower (2.94–5.11) in
Fig. 1. Total COD (TCOD) and soluble COD (SCOD) concentrations of raw and pretreated sludge samples; scheme-1 (FPS + TWAS) (a) and (b); scheme-2 (TWAS
only) (c) and (d); and the effect of hydrothermal pretreatment on the VSS removal efficiencies (e).
P. Zhou et al.

5. Bioresource Technology 321 (2021) 124498
5
comparison to scheme-2 (6.1–14.5). The increase of SCOD concentra­
tions after THP implies that pretreatment promoted the solubilization
rate of insoluble particulate organic matters in the sludge (Grubel et al.,
2014; Zhang et al., 2019). The disintegration and hydrolysis of partic­
ulate organics in sludge occur during the thermal pre-treatment,
resulting in the release of organics in the liquid phase, which could be
indicated by SCOD increase (Grubel et al., 2014; Park and Ahn, 2011).
The TCOD concentration of the pretreated samples should generally
remain almost constant after pretreatment (Aboulfoth et al., 2015;
Bougrier et al., 2006; Dhar et al., 2012). However, in this study, TCOD
concentrations slightly decreased after various pretreatment conditions
under both schemes. This could be attributed to the sludge accumulation
on the interior wall of the hydrothermal reactor during transfer (Bou­
grier et al., 2006). Moreover, the volatilization of organics might occur
during the thermal pretreatment (Mendez et al., 2014).
To grasp better understanding about the degree of solubilization and
the extent of sludge hydrolysis and disintegration performance after
THP; the changes in the ratio of SCOD/TCOD was calculated (Atay and
Akbal, 2016; Eskicioglu et al., 2006; Park and Ahn, 2011). As shown in
Table 3, all the pretreatment conditions caused considerable increases in
the ratios of SCOD/TCOD relative to the corresponding untreated con­
trol samples (i.e., FPS + TWAS and TWAS). In scheme-1, a maximum
increase of SCOD concentration at 160 ◦
C, 30 min led to the highest
SCOD/TCOD of 46%. Similar SCOD/TCOD ratio was also observed at
180 ◦
C, 15 min. On the other hand, in scheme-2, the highest SCOD/
TCOD ratio of 58% was observed for the THP at 180 ◦
C, 30 min. It is
worth noting that in scheme-2, COD solubilization was similar between
the conditions of 160 ◦
C, 60 min and 180 ◦
C, 15 min at ~49% (p < 0.01).
It can be explained due to the fact that both these two conditions were
under the same SI value as discussed later.
Fig. 1e shows the VSS removal efficiencies for different pretreatment
conditions. The detailed results of TSS and VSS concentrations are
provided in the Supporting materials, which demonstrated that the
application of THP under different conditions led to a considerable
reduction of suspended solids. As shown in Fig. 1e, for both schemes, the
highest VSS removal efficiencies were observed at the condition of
180 ◦
C, 60 min (i.e., 56% and 71% for scheme 1 and scheme 2,
respectively). Thus, higher temperature benefited suspended solids
solubilization. Similar solubilization levels and solids reduction (40% −
80%) were reported at the temperature range 170–190 ◦
C (Bougrier
et al., 2008). However, the impact of duration time of the pretreatment
on the reduction of suspended solids was minimal compared to the
temperature. For example, at 140 ◦
C in scheme-2, VSS and TSS con­
centrations remained almost the same at different exposure times (p =
0.803) (see Supporting materials). In most cases, higher solubilization
efficiencies were observed in scheme-2 (TWAS only) than scheme-1
(FPS + TWAS) in terms of VSS removal and SCOD solubilization (see
Fig. 1e and Table 3). It could be attributed to the differences between the
initial TS content in TWAS and TWAS + FPS (see Table 1). For instance,
a previous study by Elbeshbishy et al. (2011) suggested that the increase
in initial TS content in a feedstock could decrease solubilization effi­
ciencies during pretreatment. Moreover, it is expected that the distri­
bution of the COD fractions (e.g., proteins, lipids, and carbohydrates)
would be different in TWAS and TWAS + FPS, and could potentially
influence the effectiveness of THP, which warrants further investigation.
The correlation between the increase in SCOD/TCOD (%) with
respect to solubilization (%) in both pretreated sludge schemes was
evaluated and highlighted (see Supporting materials). The coefficient of
determination varied between 0.71 and 0.89 with very strong trend in
FPS + TWAS. Compiling both schemes lead to an average coefficient of
determination of 0.77. This finding endorses the association of the in­
crease in SCOD/TCOD (%) with increase of solubilization (%) and such
relationship using either the increase of SCOD/TCOD (%) or solubili­
zation (%) as a marker for COD solubilization can be used
interchangeably.
The main effects and interaction plots of COD solubilization in terms
of VSS removal (%), SCOD/TCOD increase (%), and temperature (◦
C)
are depicted in the matrix plot in Fig. 2a. Generally, every individual
plot shows a positive correlation between all variables regardless the
sludge and nature of substrate used. For instance, in the left column, the
overall increase of temperature lead to an increase trend in VSS removal
and SCOD/TCOD increase (%). On the contrary pinpointing the influ­
ence of the nature of sludge or substrate used, the main effects and
interaction plots varied (see Supporting materials). The FPS + TWAS
pretreated samples (see Supporting materials) showed a limited or low
interdependence between temperature and other parameters. In
contrast, the correlation matrix plot of the TWAS pretreated samples
strengthen a notion of significant influence of the sludge or substrate
with a strong correlation (high interdependence) between all variables
(see Supporting materials).
To better elucidate this finding, we plotted the correlation between
the SCOD/TCOD ratio (%), increase in solubilization (%), and VSS
removal efficiency (%) as a function of the severity index (SI) (Fig. 2 b
and c). SI range (2.4–4.1) for the various pretreatment temperature and
exposure time is illustrated in Table 2. Overall, the increase of the
SCOD/TCOD ratio and VSS removal efficiencies was observed with the
increase of SI. Specifcally, for scheme-2 (TWAS only), COD solubiliza­
tion, and VSS removal efficiencies showed a strong linear correlation
with SI (R2
> 0.9). In accordance with the findings of this study, Kakar
et al. (2019) reported a positive correlation between SI and COD solu­
bilization for sourced-separated organics at five SI values (Kakar et al.,
2019). Nevertheless, such a strong correlation was not noticed for
scheme-1 (FPS + TWAS), which can be attributed to the difference in
sludge characteristics (FPS + TWAS vs. TWAS). For instance, the
macromolecular composition (proteins, lipids, and carbohydrates) of
FPS and TWAS would be distinct. These macromolecular components
are known to respond differently under various temperatures used for
THP (Barber, 2016), which could possibly explain such a weak corre­
lation between SI and COD solubilization or VSS removal efficiencies.
Table 3
Summary of SCOD/TCOD ratio and percentage of solubilization for different
pretreatment conditions.
Experimental conditions SCOD/TCOD
(%)
Solubilization
(%)
Scheme 1 (FPS +
TWAS)
(FPS + TWAS) 140 ◦
C,
15 min
29 21
(FPS + TWAS) 140 ◦
C,
30 min
34 22
(FPS + TWAS) 140 ◦
C,
60 min
30 19
(FPS + TWAS) 160 ◦
C,
15 min
29 21
(FPS + TWAS) 160 ◦
C,
30 min
46 40
(FPS + TWAS) 160 ◦
C,
60 min
41 31
(FPS + TWAS) 180 ◦
C,
15 min
46 39
(FPS + TWAS) 180 ◦
C,
30 min
38 31
(FPS + TWAS) 180 ◦
C,
60 min
39 25
Scheme 2 (TWAS
only)
TWAS (140 ◦
C, 15 min) 32 20
TWAS (140 ◦
C, 30 min) 30 19
TWAS (140 ◦
C, 60 min) 45 29
TWAS (160 ◦
C, 15 min) 40 33
TWAS (160 ◦
C, 30 min) 45 34
TWAS (160 ◦
C, 60 min) 49 34
TWAS (180 ◦
C, 15 min) 49 34
TWAS (180 ◦
C, 30 min) 58 34
TWAS (180 ◦
C, 60 min) 55 49
Untreated FPS 13 NA
Untreated samples Untreated TWAS 4 NA
Untreated FPS + TWAS 9 NA
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6. Bioresource Technology 321 (2021) 124498
6
For instance, compared to lipids, THP is reported to be more efficient for
the solubilization of carbohydrates and proteins (Barber, 2016), while
primary sludge usually contains more lipids (Wilson and Novak, 2009).
Therefore, further investigation incorporating the comprehensive
characterization of these macromolecular compounds would be essen­
tial to get more insights into such observation. In summary, THP showed
a better performance for TWAS rather than the mixture of FPS and
TWAS in terms of the sludge solubilization. The findings of this study
further strengthen the notion with past studies that THP is more effec­
tive on waste activated sludge than primary sludge (Carrère et al., 2010;
Ge et al., 2010; Mottet et al., 2009).
3.1.2. Variations of VFAs and ammonia nitrogen
Fig. 3a shows the concentrations and distribution of total and
individual VFAs (acetate, propionate, and butyrate) in various sludge
samples. The overall trend showed an increase in VFAs concentration
after all pretreatment conditions. Notably, VFAs concentrations
increased with increasing of the temperature in most of the conditions
except at 140 ◦
C. At 140 ◦
C in scheme-1, the portions of acetate, pro­
pionate, and butyrate were quite similar under various exposure times
(p = 0.991, statistically insignificant). In both schemes, the pretreatment
at 180 ◦
C contributed to the highest increase of VFAs concentrations
(acetate: 1693 ± 57 mg COD/L and 1157 ± 39 mg COD/L, propionate:
1134 ± 55 mg COD/L and 455 ± 36 mg COD/L, butyrate: 1001 ± 34 mg
COD/L and 440 ± 23 mg COD/L, respectively).
In contrast, the exposure time showed a little impact on VFAs pro­
duction; VFAs concentrations remained almost constant under various
exposure times. The rise in VFAs concentration could be correlated to
Fig. 2. (a) Matrix Plot of SCOD/TCOD increase (%), VSS removal (%), and Temperature (◦
C); and VSS removal efficiency (%), sludge solubilization (%) and increase
of SCOD/TCOD (%) as a function of severity index (SI) in (b) scheme-1: FPS + TWAS, and (c) scheme-2: TWAS only.
P. Zhou et al.

7. Bioresource Technology 321 (2021) 124498
7
the degradation of lipids (Bougrier et al., 2008) and other extracellular
polymeric substances such as polysaccharides and humic acids in
addition to the solubilization of intracellular organics or proteins (Kor-
Bicakci and Eskicioglu, 2019). It is interesting to note that the THP
promote the destruction of cell walls and cell membranes that further
enhance the biological degradation of proteins (Appels et al., 2010).
Wilson and Novak (2009) performed a laboratory simulation of THP on
PS and WAS in terms of proteins, lipids, and polysaccharides. In their
study, more VFAs were produced from PS, and it was associated with the
hydrolysis of unsaturated lipids (Wilson and Novak, 2009). In fact, the
initial VFAs level was considerably higher in FPS than TWAS (see
Table 1).
An appropriate ammonia level is quite essential in the AD process in
order to maintain the system stability and provide buffer capacity for
active microbial activities (Angelidaki and Sanders, 2004; Ryue et al.,
2020). However, high ammonia levels result in system toxicity and
further inhibit AD performance (Lin et al., 2018). Fig. 4 shows the
concentration of total ammonia nitrogen (TAN) in the untreated and
pretreated sludge. An obvious increase in TAN concentrations was
observed after all the pretreatment conditions; TAN concentrations
increased with the increase in temperature. The highest ammonia con­
centration occurred at the condition of 180 ◦
C, 15 min at 361 ± 14 mg/L
Fig. 3. Impact of the pretreatment conditions on VFAs production in terms of (a) the concentrations of total VFAs and individual VFAs (Acetate, Propionate,
Butyrate), and (b) (%) relative distribution of individual VFAs.
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8. Bioresource Technology 321 (2021) 124498
8
in scheme-1, and the condition of 180 ◦
C, 60 min at 468 ± 12 mg/L in
scheme-2. Notably, at 160–180 ◦
C, increases in TAN concentrations in
scheme-2 (TWAS only) were slightly higher than those observed for
scheme-1 (FPS + TWAS). This observation could be attributed to the
hydrolysis of proteinaceous organic materials while TWAS usually have
more proteins than primary sludge (Wilson and Novak, 2009). None­
theless, under both conditions, TAN concentrations remained lower than
inhibitory TAN concentrations of 4.2 g/L reported for methanogenic
strains isolated from sludge anaerobic digesters (Jarrell et al., 1987).
3.2. Methane potential and kinetics
3.2.1. Methane yields
Fig. 5 shows cumulative methane yields in mL CH4/g COD for
different test conditions. The BMP test was terminated after 25 days
when the methane production became nearly negligible for most of the
samples, except few conditions such as 140 ◦
C, 30 min, and 160 ◦
C,
15–60 min in scheme-1. According to these results, the methane yield
was increased by 9–161%, depending on the pretreatment conditions. In
scheme-1 (Fig. 5a), the maximum methane yield of 272 mL CH4/g COD
was obtained under a pretreatment condition of 160 ◦
C, 60 min. The
increase was 161% or 2.62-fold higher than that of the control digester
(104 mL CH4/g COD). In scheme-2 (Fig. 5b), the highest biomethane
yield of 182 mL CH4/g COD was achieved at the condition of 140 ◦
C, 30
min, which was 75% greater than that of the control one (104 mL CH4/g
COD). Following the untreated sludge, the lowest methane production
belonged to the condition of 180 ◦
C, 60 min for both schemes. It is worth
mentioning that the different trends of the impacts of THP on the sludge
solubilization and biomethane production were observed. Notably, the
increase of the SCOD and the decrease in the methane production was
found for a given condition of 180 ◦
C. Previous studies also suggested
that some soluble non-biodegradable organics could be produced under
severe THP conditions (i.e., high temperatures) such as melanoidins
(Appels et al., 2010; Luo et al., 2019).
Generally, different patterns in methane production, as well as the
cumulative methane yields, were observed depending on the range of
pretreatment temperatures and exposure times used. For both schemes,
samples treated under 160 ◦
C and 180 ◦
C generally showed extended lag
phases, as compared to samples treated at 140 ◦
C. Interestingly, the
untreated control sample’s lag phase was comparatively shorter than
most of the pretreated samples (Fig. 5). However, except for samples
treated at 180 ◦
C, most of the pretreated samples ultimately provided
higher methane yields than the control. These results indicated that
microbial communities gradually adopted the thermally hydrolyzed
sludge; it took longer than the control to achieve their maximum
methane production rate. A previous study also suggested that methane
production increased as the THP temperature increased until a threshold
temperature is reached, above which the methane production decreased
(Bougrier et al., 2008; Higgins et al., 2017; Mottet et al., 2009; Razavi
et al., 2019). This is usually ascribed to the Maillard reactions, where
carbohydrates and amino acids form melanoidins at high temperature,
which are difficult or impossible to degrade (Carrère et al., 2010).
Sludge samples from scheme-1 (THP of FPS + TWAS at 140–160 ◦
C)
and scheme-2 (THP of TWAS at 140 ◦
C) provided higher methane yield
and higher production rate than the control than the control (Table 4
and Fig. 5). The maximum methane yield from scheme-1 (FPS + TWAS;
272 mL CH4/g COD) was higher than scheme-2 (TWAS only; 182 mL
CH4/g COD). This can be attributed to the fact that FPS could encompass
a higher level of readily biodegradable organics, such as VFAs, which
further increased via THP in scheme-1 (see Fig. 3a). However, methane
production improvement varied widely without any specific trends for
different temperatures and exposure times. Different temperatures and
exposure times can lead to the same SI value (see Table 2). Therefore,
the relationship between methane production and SI was further
assessed (Fig. 6). For both schemes, methane potential showed a linear
relationship with SI values. It was evident that higher SI values nega­
tively affected methane yield for both scenarios. Although higher tem­
peratures and longer retention time largely increased sludge
solubilization, it did not show considerable improvement in terms of
biomethane yields. Similar results were also found by Razavi et al.
(2019) for THP of source-separated organics. They investigated THP
under five SI values (3, 3.5, 4, 4.5, and 5). From their findings, the
maximum methane production rate decreased with the increase of the SI
values (Razavi et al., 2019).
To explore potential interactions among various process parameters,
the biplot and score plots were also established from the principal
component analysis (PCA) (see Supporting materials). Briefly, PCA
examined the variations of the different sludge samples from THP in
terms of major parameters temperature, solubilization (%), SCOD/
TCOD (%), VSS removal (%), and total cumulative methane production.
The respective contribution to the total variance in PCA analysis was
manifested by the percentages of variations along with PC-1 or PC-2.
The THP treated samples were visibly separated by PC axis 1 with
75% of the variations (highest variations) and distributed along axis 2
(the second most variations in samples, 12%). The pre-treated TWAS
samples at temperatures 160 ◦
C and 180 ◦
C at different exposure times
were clustered together (top right of the plot), indicating the similarity
of these conditions. However, THP treated samples at 140 ◦
C under
different exposure times were marginally separated and deviated in
another quadrant (i.e., 15 min and 30 min were clustered in the top left
and 60 min were placed near to the origin vertical line). On the other
hand, pre-treated FPS + TWAS samples were gradually scattered along
both axes and mostly PC1. This clearly implies that the treatment con­
ditions of the samples were gradually altered based on sludge charac­
teristics. Moreover, a positive relationship of SCOD/TCOD (%) and VSS
removal (%) with the TWAS samples was observed (see Supporting
materials). The associations of solubilization (%) and temperature were
positive direction of PC1 and the FPS + TWAS part. Nevertheless, the
total methane production was slightly placed in the origin axis between
the top and bottom of left plots and the negative direction of PC1. This
can be attributed due to the association of high methane yield to con­
ditions such as (FPS + TWAS) 140 ◦
C, 15 min, (FPS + TWAS) 140 ◦
C, 30
min and (FPS + TWAS) 160 ◦
C, 60 min.
Fig. 4. Effect of the pretreatment conditions on the variations of the concen­
tration of total ammonia nitrogen (TAN).
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9. Bioresource Technology 321 (2021) 124498
9
For better illustrations to highlight all correlations of the parameters
with the sludge samples, the PCA was reexamined considering eight
major parameters: temperature, exposure time, solubilization (%),
SCOD/TCOD (%), VSS removal (%), VFAs, ammonia (TAN), and total
cumulative methane production (see Supporting materials). As expected
from previous PCA plots, the quadrant’s arrangement was a bit similar in
terms of scattering the samples on the four parts (top quadrants for
TWAS and bottom quadrants for FPS + TWAS). Additionally, the re­
lationships of all five parameters were mostly similar. This can be
manifested by the same positive relationship of SCOD/TCOD (%) and
VSS removal (%) with the TWAS samples (i.e., samples with high VSS
removal) and the associations of solubilization (%) and temperature in
the positive direction of PC1 and the FPS + TWAS part.
The additional observations can be summarized as follows: the pro­
duction of ammonia was positively correlated with the FPS + TWAS at
160 and 180 ◦
C (15, 30, and 60 min), and TWAS at 180 ◦
C (15, 30, and
60 min) samples. Similarly, the production of VFAs was positively
associated with the FPS + TWAS at 180 ◦
C (15 min, 30 min, and 60 min)
samples. The other observation includes the slight altering in the
orientation of the total cumulative methane production in the PC 2 axis
direction (i.e., this led to the increase in the variations of this direction).
This can be attributed due to the high association of methane yields with
the two maximum values observed for conditions of FPS + TWAS
samples at 160 ◦
C (60 min) and 140 ◦
C (30 min). The above stated ob­
servations can lead to the rationale change in the PC1 and PC2 distri­
butions 58 and 19% respectively in comparison to the 75 and 12%
respectively.
For the FPS + TWAS samples, it can be observed that factors such as
methane yields and VFAs production were positively impacted by the
variations of operational parameters, such as increasing temperature
and time up to 160 ◦
C and 60 min. In contrast, for the TWAS samples, it
can be remarked the positive impact of increasing both temperature and
time up to 180 ◦
C and 60 min with the increase of solubilization, VSS
removal, and TAN. Overlooking the reduction of methane yields in the
Fig. 5. The time-course profile of cumulative methane yield for (a) scheme-1 (pretreated FPS and TWAS), and (b) scheme-2 (untreated FPS in addition to TWAS).
Note. Methane yields were calculated based on the initial COD of substrate added.
P. Zhou et al.

10. Bioresource Technology 321 (2021) 124498
10
TWAS due to the increase of TAN production from hydrolysis of
proteinaceous organic materials (Wilson and Novak, 2009), the indica­
tion of THP effectiveness in solubilization for TWAS compared to FPS
can be substantiated.
In summary of the given results, the PCA endorsed the same obser­
vations of earlier sections relevant to the various conditions (i.e., sludge
substrate, temperature, and exposure time) that favored an increase in
solubilization and increase in production of VFAs and ammonia and
methane. Hence, PCA can be employed for the differentiation of pre­
treatment conditions and to assess the variability of pretreatment con­
ditions in terms of temperature, exposure time, solubilization (%),
SCOD/TCOD increase (%), VSS removal (%), VFA, TAN, and methane
yield.
3.2.2. Methanogenesis rates
Table 4 summarizes the estimated methanogenesis rate constant (k)
using the first-order kinetic model. Interestingly, most of the pretreat­
ment conditions under both schemes showed lower k values than the
control. In scheme-1, the maximum k value was achieved at 140 ◦
C and
60 min (0.122 /d), which was still lower than the control (0.158 /d). In
contrast, two pretreatment conditions in scheme-2 showed k values
comparable to the control. The maximum k values were observed for the
condition of 140 ◦
C, 30 min (0.165/d), followed by 140 ◦
C, 15 min
(0.159/d). Despite lower k values, in most cases, THP at 140–160 ◦
C
ultimately gave higher methane yields than the control, suggesting that
THP samples took a longer time than the control to achieve the
maximum methane production rates. Therefore, the modified Gompertz
Table 4
The estimated kinetic parameters from BMP test results using the first-order and modified Gompertz models.
BMP test conditions First-order Model Modified Gompertz Model
Methanogenesis rate
constant, k (d-1
)
Standard error
for k
Maximum methane
production rate, R (mL/d)
Standard error
for R
Lag phase,
λ (d)
Standard error
for λ
Scheme 1 (FPS
+ TWAS)
(FPS + TWAS)
140 ◦
C, 15 min
0.077 0.006 142.53 10.39 2.98 0.61
(FPS + TWAS)
140 ◦
C, 30 min
0.081 0.006 184.33 10.62 2.28 0.49
(FPS + TWAS)
140 ◦
C, 60 min
0.122 0.005 162.58 3.68 0.42 0.16
(FPS + TWAS)
160 ◦
C, 15 min
0.090 0.005 131.41 5.66 1.22 0.38
(FPS + TWAS)
160 ◦
C, 30 min
0.045 0.005 96.58 9.04 8.67 0.71
(FPS + TWAS)
160 ◦
C, 60 min
0.055 0.006 175.79 18.46 8.62 0.67
(FPS + TWAS)
180 ◦
C, 15 min
0.054 0.004 39.80 3.77 2.49 1.07
(FPS + TWAS)
180 ◦
C, 30 min
0.055 0.006 66.24 8.16 6.13 1.04
(FPS + TWAS)
180 ◦
C, 60 min
0.041 0.005 42.21 5.67 9.06 1.06
Scheme 2 (TWAS
only)
TWAS (140 ◦
C, 15
min) + FPS
0.159 0.003 185.65 7.86 − 0.49 0.26
TWAS (140 ◦
C, 30
min) + FPS
0.165 0.002 184.17 6.83 − 0.71 0.23
TWAS (140 ◦
C, 60
min) + FPS
0.090 0.005 78.62 3.53 1.09 0.39
TWAS (160 ◦
C, 15
min) + FPS
0.094 0.005 69.38 2.24 0.88 0.28
TWAS (160 ◦
C, 30
min) + FPS
0.091 0.004 34.74 1.52 − 0.93 0.46
TWAS (160 ◦
C, 60
min) + FPS
0.080 0.005 46.35 3.28 0.09 0.74
TWAS (180 ◦
C, 15
min) + FPS
0.057 0.005 47.99 4.52 4.75 0.87
TWAS (180 ◦
C, 30
min) + FPS
0.061 0.005 53.48 4.87 3.76 0.87
TWAS (180 ◦
C, 60
min) + FPS
0.072 0.004 24.21 1.98 − 0.97 0.99
Control Untreated FPS +
TWAS
0.158 0.004 94.54 2.74 − 0.21 0.17
Fig. 6. Methane potential as a function of severity index (SI) for scheme-1
(pretreated FPS and TWAS), and scheme-2 (untreated FPS + treated TWAS).
P. Zhou et al.

11. Bioresource Technology 321 (2021) 124498
11
kinetic model was further used to estimate maximum methane pro­
duction rates (R) and lag phase times (λ).
In scheme-1 (FPS + TWAS), except for 180 ◦
C, estimated R values
were mostly higher than the control (see Table 4). Also, λ values were
higher than the control for all cases. Thus, for scheme-1, higher R values
for conditions under 140 ◦
C and 160 ◦
C led to higher cumulative bio­
methane yield than the control. In scheme-2, only two THP conditions
(140 ◦
C, 15–30 min) showed R values higher than the control. These
conditions also showed k values (estimated with the first-order model)
comparable to the control (see Table 4). Interestingly, for most of the
conditions, λ values for scheme-2 (TWAS only) were close to that
observed for the control and considerably lower than the values esti­
mated for scheme-1 (FPS + TWAS). It should be noted that negative lag
phases observed for a few conditions in scheme-2 and the control,
indicating no adoption time required for those specific conditions, as
previously reported in the literature (Çelekli et al., 2008).
Despite superior kinetics over some THP conditions, control (un­
treated sludge) provided substantially lower cumulative biomethane
yield than sludge samples from scheme-1 (THP of FPS + TWAS at
140–160 ◦
C) and scheme-2 (THP of TWAS at 140 ◦
C) (see Fig. 5). The
cumulative methane yield for the control reached a plateau within 10
days; the total digestion time was maintained the same for all conditions
(25 days). Generally evaluating the THP influence on the kinetic pa­
rameters for both schemes, an adverse impact can be primarily noted,
excluding two conditions in scheme-2 (140 ◦
C; 15 and 30 min). Inter­
estingly, Koupaie et al. (2017) applied microwave pretreatment to
TWAS and reported higher k values for all pretreatment conditions
compared to the untreated one (Hosseini Koupaie et al., 2017). Another
study reported an increase of k values after THP of source-separated
organics (Azizi et al., 2019). The dissimilarity of the k values might be
due to the nature of the substrates and the application of different pre­
treatment methods. For better understanding about the underlying
mechanism behind such observation would require further investiga­
tion. Overall, the kinetic analysis suggests the slow microbial adoption
of THP sludges led to extended digestion time over the control, which
can be overcome or minimized in digesters’ continuous operation. This
necessitates further research to be conducted with long-term continuous
anaerobic digestion tests.
3.3. Significance of results and outlook
Two process schemes were assessed for incorporating THP in a
WWTP with the primary sludge fermentation process. Apparently, THP
of FPS + TWAS has been found to be more effective for enhancing
methane yield, although some performance metrics (e.g., VSS removal
efficiencies, increase in SCOD/TCOD ratios) indicated that THP would
be more effective for TWAS alone. Consistent with previous studies,
higher SI values negatively affected methane production. Interestingly,
while analyzing the process kinetics, THP appeared to adversely affect
methanogenesis rates. For instance, THP of FPS + TWAS under all
conditions showed considerably lower methanogenesis rates over the
control but ultimately provided higher methane yields for samples
treated under 140 and 160 ◦
C, which was attributed to the maximum
methane production rates (see Table 4). Thus, despite some initial
disturbance (indicated by extended lag phases), methanogenic com­
munities ultimately adopted THP samples and led to more methane
yields. Thus, long-term continuous studies with microbial character­
ization would be required to understand underlying fundamentals as
well as to approach further engineering developments of THP for
WWTPs with primary sludge fermentation.
Considering various performance matrices that have been proposed
in the literature for the evaluation of sludge solubilization, the PCA
analysis suggested that the sample treatment conditions cluster can be
gradually altered based on sludge characteristics. The PCA endorsed the
same observations related to the variations of treatment conditions fa­
voring either an increase in the solubilization and VSS (TWAS samples)
or increase in VFAs and methane (FPS + TWAS). Thus, the PCA can be
deployed in the distinction between pretreatment alternatives. Howev­
er, some performance matrices not considered in this assessment might
have a higher importance in predicting THP effectiveness. For instance,
considering detailed macromolecular composition (i.e., proteins, lipids,
and carbohydrates) would be critical to get fundamental insights into
the differences observed between the two schemes studied here.
Although THP enhanced biomethane potential, a comprehensive
mass and energy balance should be done for further evaluation. For
instance, steam demand has a linear relationship with inlet sludge
temperature (Barber, 2016). Thus, steam demand may substantially
increase at winter temperatures in cold regions. Despite several full-
scale installations, the feasibility of THP is quite case-specific.
Increasing solids content in sludge prior to THP may be considered to
reduce the steam demand, while excessive thickening may lead to heat
transfer limitations (Barber, 2016). Thus, future research is needed to
further explore these aspects for the application of THP in WWTPs with
primary sludge fermentation.
4. Conclusions
In this study, thermal hydrolysis of both FPS + TWAS and TWAS
under different temperatures and exposure times led to considerable
sludge solubilization. A positive linear correlation was observed be­
tween COD solubilization and VSS removal with THP severity index
values for TWAS alone, while such correlation was not observed for FPS
+ TWAS. Despite the significant impact on the sludge solubilization, the
results demonstrated the negative impact of high SI on biomethane
yields in THP. Therefore, further research is recommended to examine
the optimization of less intense THP to make a tradeoff between sludge
solubilization, solids removal, and biomethane recovery from AD.
CRediT authorship contribution statement
Peijun Zhou: Conceptualization, Methodology, Formal analysis,
Data curation, Visualization, Writing - original draft, Writing - review &
editing. Mohamed N.A. Meshref: Formal analysis, Data curation,
Visualization, Writing - original draft, Writing - review & editing. Bipro
Ranjan Dhar: Conceptualization, Writing - review & editing, Supervi­
sion, Funding acquisition, Project administration.
Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Acknowledgments
This research was funded by the Collaborative Research and Devel­
opment Grant (CRD) supported by the Natural Sciences and Engineering
Research Council of Canada (NSERC) and EPCOR Water Services. The
acquisition of hydrothermal reactor used in this study was supported by
John R. Evans Leaders Fund from the Canada Foundation for Innovation
(CFI). Special thanks go to Dr. Yangang (Rick) Feng, Mr. Abdul
Mohammed, Dr. Rasha Maal-Bared, and Ms. Bing Lin from EPCOR for
their continuous support in this project. The authors would like to
acknowledge assistance from current and former lab members of Dr.
Bipro Dhar’s research group throughout this project.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.biortech.2020.124498.
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12. Bioresource Technology 321 (2021) 124498
12
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