Thermal steam-explosion is the most extended hydrolysis pretreatment to enhance anaerobic digestion of sludge. Thermal hydrolysis key parameters are temperature (T) and time (t), and the generally accepted values reported from full-scale information are: 150–230 °C and 20–60 min. This study assesses the influence of different temperature–time–flash combinations (110–180 °C, 5–60 min, 1–3 re-flashing) on the anaerobic degradation of secondary sludge through biochemical methane potential (BMP) tests. All the conditions tested presented higher methane production compared to the untreated sludge, and both solubilization (after the hydrolysis) and degradation (by anaerobic digestion) increased linearly when increasing the severity (Tt) of the pretreatment, reaching 40% solubilization and degradation of the particulate matter at 180° C–60 min. However, for the 180 °C temperature, the treatment time impacted negatively on the lag phase. No influence of re-flashing the pretreated matter was observed. In conclusion, thermal steam-explosion at short operation times (5 min) and moderate temperatures (145 °C) seems to be very attractive from a degradation point of view thus presenting a methane production enhancement similar to the one obtained at 180°C and without negative influence of the lag phase.

INTRODUCTION

Sludge production minimization and resource recovery are nowadays priority issues in modern wastewater treatment plants (WWTPs) due to stringent environmental laws on wastewater treatment and sludge disposal routes. In spite of the suitability of anaerobic digestion as the key management and valorization option, the biological nature of sludge, especially secondary, limits both digestion and dewatering. Thermal hydrolysis has proven to optimize the anaerobic digestion of biological sludge by accelerating the rate-limiting hydrolysis step, improving biogas production, volatile solids removal and sludge dewatering, preventing foam formation, and removing pathogens.

However, the reported results on performance are difficult to summarize and compare, varying depending on the sludge source and treatment conditions (Carrère et al. 2010).

According to the reviews by Carrère et al. (2010) and Hii et al. (2014) most of the laboratory- or pilot-scale studies report optimum treatment temperature in the range of 160–180°C, 180 °C being the generally accepted temperature limit to avoid inhibition by formation of refractory compounds at high temperatures (Dwyer et al. 2008; Ariunbaatar et al. 2014).

With regard to the treatment time, the range 30–60 min is mostly accepted, but recent studies (Donoso-Bravo et al. 2010) found that for the pretreatment at 170 °C temperature, the time (ranging from 5 to 30 min) did not influence sludge digestion, suggesting that long operation carried out at full scale could be unnecessary.

Regarding the effect of the flash, none of the bibliographic information analyses whether the re-flashing (repetition of sudden decompression without extra heat consumption) of sludge can enhance even further the solubilization of organic matter, thereby increasing the methane production.

From a full-scale implementation point of view, the available information on the operation conditions of the different thermal hydrolysis commercial processes (Cambi®, Biothelys®, Exelys®, TPH®, Lysotherm®, Turbotec®) shows that the operation conditions are in the generally accepted range 150–230 °C, 20–60 min and one single sudden decompression (flash). As key factors for process design and economics, the revision of these values is a matter of major interest.

This study aims at evaluating different temperature–time-flash combinations (ranging from 110 to 180 °C and 5 to 60 min) on the biochemical methane potential (BMP) of steam-exploded secondary sludge, compared to untreated samples. The results are analyzed in terms of methane yield, kinetic parameters and severity factor.

MATERIALS AND METHODS

Sludge sampling

According to Pérez-Elvira et al. (2008), the study was performed for waste activated sludge (WAS) from the municipal WWTP of Valladolid (Spain), operated at 13 day solids retention time. A single sample of sludge was thickened without polyelectrolyte to 14%TS (79%VS) before being fed to the thermal hydrolysis unit in all the batch experiments performed.

The anaerobic inoculum for the BMP tests was sampled from the anaerobic digester in the WWTP treating mixed sludge, and pre-incubated for 2 days at 35 °C in a thermostated chamber prior to use in order to activate the micro-organisms and to deplete most of the residual organic matter.

Steam explosion pretreatment, operation variables and experimental set-up

The thermal hydrolysis pilot plant operated (Figure 1) consists of a 20 L hydrolysis reactor heated with live steam (12 bar) from a boiler, and connected to an atmospheric flash tank (100 L) by a decompression valve that opens in a steam-explosion effect (sudden decompression). The operation is batch, and automatically controlled by fixing both temperature and hydrolysis time.

Figure 1

Thermal pretreatment system (Fernández-Polanco et al. 2008).

Figure 1

Thermal pretreatment system (Fernández-Polanco et al. 2008).

To obtain the experimental plan (Table 1), a response surface methodology with Box–Behnken experimental design was used in this work. Three factors at two levels were considered: temperature (110° and 180 °C), time (5 and 50 min) and number of flashes (1 and 3). This last variable was evaluated by re-flashing the treated sludge twice or three times. The experimental plan consisted of 15 runs, including three repetitions at the center point of the experimental design.

Table 1

The Box–Behnken experimental design for thermal hydrolysis with three independent variables

  T (°C) t (min) log R0 Number of flashes 
CONTROL − − 
TH-1 110 1.0 
TH-2 110 30 1.8 
TH-3 110 30 1.8 
TH-4 110 50 2.0 
TH-5 145 2.0 
TH-6 145 2.0 
TH-7 145 30 2.8 
TH-8 145 30 2.8 
TH-9 145 30 2.8 
TH-10 145 50 3.0 
TH-11 145 50 3.0 
TH-12 180 3.1 
TH-13 180 30 3.8 
TH-14 180 30 3.8 
TH-15 180 50 4.1 
  T (°C) t (min) log R0 Number of flashes 
CONTROL − − 
TH-1 110 1.0 
TH-2 110 30 1.8 
TH-3 110 30 1.8 
TH-4 110 50 2.0 
TH-5 145 2.0 
TH-6 145 2.0 
TH-7 145 30 2.8 
TH-8 145 30 2.8 
TH-9 145 30 2.8 
TH-10 145 50 3.0 
TH-11 145 50 3.0 
TH-12 180 3.1 
TH-13 180 30 3.8 
TH-14 180 30 3.8 
TH-15 180 50 4.1 

Anaerobic digestion tests

BMP assays at 35 °C were conducted in triplicate in 160 mL serum bottles filled with 50 mL of a mixture of anaerobic inoculum and the corresponding substrate (untreated or treated secondary sludge) at a substrate to inoculum ratio of 0.5 g/g (on volatile solids (VS) basis). In this test, micronutrients and macronutrients were used for optimal function of anaerobic micro-organisms. Moreover, NaHCO3 and Na2S were added to provide a buffer capacity and avoid aerobic conditions, respectively. The methodology used was the one suggested by Angelidaki et al. (2009).

The bottles were closed with butyl septa, sealed with aluminum caps, purged with helium for 5 min and incubated in a thermostated chamber at 35 °C in an orbital shaker at 150 rpm/min. Methane production in the BMP assays was determined by periodic measurements of pressure and biogas composition in the headspace of the bottles. Reference tests containing only anaerobic inoculum were prepared to determine the endogenous methane production of the inoculum, which was subtracted from the total methane production in the BMP tests to obtain the real methane production of the substrate. The experimental values obtained are always referred to average values, with the corresponding standard deviation.

Performance parameters

Table 2 summarizes the target parameters calculated.

Table 2

Prediction parameters for the evaluation of TH

Parameter Symbol Units Equation 
Severity factor log R0 −  
Solubilization factor SF  
Methane potential CH4 mL CH4/g VSfed  
Biodegradability BD  
Degradation factor DF  
Parameter Symbol Units Equation 
Severity factor log R0 −  
Solubilization factor SF  
Methane potential CH4 mL CH4/g VSfed  
Biodegradability BD  
Degradation factor DF  

It is worth mentioning that both solubilization and degradation factors (SF and DF) are calculated with respect to the particulate fraction of the chemical oxygen demand (COD), in contrast to most of the references that express these parameters with respect to the total COD. These proposed expressions are more accurate as the particulate matter is the potentially hydrolyzable fraction during the pretreatment.

And sludge biodegradability (BD) was calculated as the ratio of the experimental (mL CH4/gCOD) to the theoretical methane production (350 mLCH4/gCODremoved).

Modelling

Four models were considered to fine-tune the experimental data from BMP tests to theoretical equations in order to estimate kinetic parameters with a certain degree of confidence.

Based on similar studies with solid wastes (Cano Herranz 2014), the models considered were (see Table 3): first order equation (FO), Modified Gompertz (MG) equation, transference function (TF), and logistic function (LF).

Despite differing mathematically from each other, the four models have common features: a kinetic parameter (Rm or μmax) which indicates the maximum slope of the curve (mL CH4/gVS/d), a maximum biogas production parameter (P) expressed as mL CH4/gVS, and a lag-phase parameter (λ), in days. B is the calculated methane production (mL CH4/gVS) for each time t. The correlation factor (R2) was also calculated to assess the accuracy of each model with respect to the experimental data.

Analytical methods

Total solids (TS), VS, total chemical oxygen demand (TCOD) and soluble chemical oxygen demand (SCOD) concentrations were determined according to Standard Methods (Eaton et al. 2005). The soluble phase for SCOD was obtained by centrifugation at 5,000 rpm for 10 min. The pressure in the headspace of the BMP bottles was measured with a pressure sensor PN 5007 (IFM, Germany), and biogas composition was determined using a gas chromatograph coupled with a thermal conductivity detector (Varian CP-3800, USA).

RESULTS AND DISCUSSION

Evaluation of thermal hydrolysis operation parameters through BMP test curves

Figure 2 presents the digestion curves obtained in the BMP tests: Figure 2(a), (b) and (c) the influence of temperature and time, whereas Figure 2(d) the influence of re-flashing.

Figure 2

Methane production curves from BMP test of the pretreated samples at 110 °C (a), 145 °C (b) and 180 °C (c), and after re-flashing (d).

Figure 2

Methane production curves from BMP test of the pretreated samples at 110 °C (a), 145 °C (b) and 180 °C (c), and after re-flashing (d).

The first evidence of these experimental results obtained is that all the conditions tested presented higher methane production in the final values for day 30 compared to the control (untreated sample), from 20% improvement (at 110 °C) to 40% (at 180 °C). Surprisingly, time was not a relevant parameter, the results for the different temperatures tested being rather similar for pretreatments at 110 and 145 °C (Figure 1(a) and 1(b)). Only at 180 °C did the pretreatment time influence negatively the lag phase (see kinetic parameters in Table 2).

Therefore, thermal steam-explosion at short operation times (5 min) and moderate temperatures (145 °C) seems to be very attractive from a degradation point of view, thus presenting a methane production enhancement similar to the one obtained at 180°C and without negative influence of the lag phase.

Figure 2(d)) clearly exhibits that neither time nor re-flashing influenced the methane production.

Evaluation of modeling accuracy

The modeling approach was performed for all the samples, showing generally a good accuracy except for the tests with lag-phase. To summarize and focus the discussion, the results presented below correspond only to three samples: the untreated (CONTROL), TH-1 (pretreated, with no lag-phase) and TH-15 (pretreated, with lag-phase).

Table 4 summarizes the results of the estimated parameters obtained with the four models, and Figure 2 presents the model fit to the experimental BMP curves.

Table 4

Estimated parameters by the four models for control, TH-1 and TH-15 samples

    Model
 
Sample Estimated parameters MG TF LF FO 
CONTROL P (mL CH4/gSfed226 238 221 239 
Rm (mL CH4/gSVfed/d) 37.4 52.0 39.9 − 
λ (d) 0.105 0.109 0.387 − 
μ max (d−1− − − 0.209 
R2 0.971 0.988 0.955 0.988 
TH-1 P (mL CH4/gSfed274 287 269 288 
Rm (mL CH4/gSVfed/d) 43.3 60.8 46.7 − 
λ (d) 0.077 0.066 0.403 − 
μ max (d−1− − − 0.206 
R2 0.982 0.994 0.969 0.993 
TH-15 P (mL CH4/gSfed288 348 282 374 
Rm (mL CH4/gSVfed/d) 41.7 30.4 48.8 − 
λ (d) 3.30 0.990 3.91 − 
μ max (d−1− − − 0.067 
R2 0.995 0.948 0.991 0.943 
Average R2 all samples 0.989 0.986 0.981 0.985 
    Model
 
Sample Estimated parameters MG TF LF FO 
CONTROL P (mL CH4/gSfed226 238 221 239 
Rm (mL CH4/gSVfed/d) 37.4 52.0 39.9 − 
λ (d) 0.105 0.109 0.387 − 
μ max (d−1− − − 0.209 
R2 0.971 0.988 0.955 0.988 
TH-1 P (mL CH4/gSfed274 287 269 288 
Rm (mL CH4/gSVfed/d) 43.3 60.8 46.7 − 
λ (d) 0.077 0.066 0.403 − 
μ max (d−1− − − 0.206 
R2 0.982 0.994 0.969 0.993 
TH-15 P (mL CH4/gSfed288 348 282 374 
Rm (mL CH4/gSVfed/d) 41.7 30.4 48.8 − 
λ (d) 3.30 0.990 3.91 − 
μ max (d−1− − − 0.067 
R2 0.995 0.948 0.991 0.943 
Average R2 all samples 0.989 0.986 0.981 0.985 

Table 4 shows that in most cases the estimated parameters were determined with a high degree of confidence (R2 = 0.98). Regarding the maximum methane production, the four models estimate similar values in all the tests. However, some differences can be observed among the different models. FO estimates the micro-organisms' growth velocity (μmax), which cannot be compared to the maximum methane production rate (Rm), which is estimated by the other models. While TF tends to overestimate this parameter, LF and MG estimate more similar values. Donoso-Bravo et al. (2010) also found this coincidence between LF and MG models.

Regarding the lag-phase, it is only determined by all the tri-parametrical models (MG, TF and LF), but only MG and LF fine-tune correctly this kind of kinetic. Table 4 shows that in the test with 3–4 day lag-phase (TH-15), TF and FO exhibited a poor correlation (R2 = 0.948 and 0.943, respectively), showing that these models do not fit lag-phase kinetics. This experimental evidence is very clear in Figure 3, where only MG and LF follow accurately the experimental points in TH-15, and is consistent with the experimental results of Cano Herranz (2014) performed with grease waste.

Figure 3

Experimental (points) and estimated (lines) methane production curves.

Figure 3

Experimental (points) and estimated (lines) methane production curves.

Comparing the accuracy of the four models, the final conclusion is that the MG equation results to be in general the most appropriate to fine-tune thermal hydrolyzed secondary sludge kinetics, showing an average regression coefficient R2 of 0.989. Similar accuracy values were obtained by Donoso-Bravo et al. (2010) and Cano Herranz (2014) with solid substrates and thermally pretreated sludge, respectively.

Relationship between pretreatment severity and performance parameters

Most of the studies on thermal hydrolysis of secondary sludge report that it is an effective pretreatment method to improve anaerobic digestion kinetics and methane production from sludge (Wilson & Novak 2009; Oosterhuis et al. 2014; Zhang et al. 2014). However, the quantification of this improvement is difficult to measure by the sole observation of BMP curves and the information that could be extracted can be inaccurate.

Therefore, Table 5 summarizes for the different operation conditions the prediction parameters calculated from the experimental curves (SF, methane, BD and DF), together with the parameters obtained with the application of the MG (which was the most accurate).

Table 5

Experimental set-up and corresponding results

  Pretreatment
 
  Anaerobic digestion
 
Kinetics
 
 T °C t min Number of° flashes SF % CH4 mL/gVS BD % DF % P mL CH4/gVS Rm mL CH4/gVS/d λ d R2-- 
CONTROL − − 250 47 226 37.4 0.10 0.971 
TH-1 110 298 56 22 274 43.3 0.08 0.982 
TH-2 110 30 15 311 59 27 288 55.7 0.24 0.985 
TH-3 110 30 15 298 57 22 277 45.4 0.41 0.989 
TH-4 110 50 21 303 57 24 284 49.4 0.21 0.989 
TH-5 145 19 319 60 31 295 54.4 0.27 0.986 
TH-6 145 18 316 60 30 298 51.6 0.32 0.991 
TH-7 145 30 23 322 61 33 300 60.7 0.35 0.988 
TH-8 145 30 18 316 60 30 299 51.4 0.44 0.993 
TH-9 145 30 25 314 59 29 298 50.3 0.51 0.994 
TH-10 145 50 27 315 60 30 291 57.0 0.28 0.986 
TH-11 145 50 27 315 60 30 299 52.6 0.42 0.993 
TH-12 180 28 313 59 29 301 48.2 0.89 0.993 
TH-13 180 30 34 344 65 42 297 59.7 0.69 0.996 
TH-14 180 30 41 340 64 41 302 41.4 2.05 0.998 
TH-15 180 50 39 338 64 40 288 41.7 3.30 0.995 
  Pretreatment
 
  Anaerobic digestion
 
Kinetics
 
 T °C t min Number of° flashes SF % CH4 mL/gVS BD % DF % P mL CH4/gVS Rm mL CH4/gVS/d λ d R2-- 
CONTROL − − 250 47 226 37.4 0.10 0.971 
TH-1 110 298 56 22 274 43.3 0.08 0.982 
TH-2 110 30 15 311 59 27 288 55.7 0.24 0.985 
TH-3 110 30 15 298 57 22 277 45.4 0.41 0.989 
TH-4 110 50 21 303 57 24 284 49.4 0.21 0.989 
TH-5 145 19 319 60 31 295 54.4 0.27 0.986 
TH-6 145 18 316 60 30 298 51.6 0.32 0.991 
TH-7 145 30 23 322 61 33 300 60.7 0.35 0.988 
TH-8 145 30 18 316 60 30 299 51.4 0.44 0.993 
TH-9 145 30 25 314 59 29 298 50.3 0.51 0.994 
TH-10 145 50 27 315 60 30 291 57.0 0.28 0.986 
TH-11 145 50 27 315 60 30 299 52.6 0.42 0.993 
TH-12 180 28 313 59 29 301 48.2 0.89 0.993 
TH-13 180 30 34 344 65 42 297 59.7 0.69 0.996 
TH-14 180 30 41 340 64 41 302 41.4 2.05 0.998 
TH-15 180 50 39 338 64 40 288 41.7 3.30 0.995 

As previously stated, thermal pretreatment improved the anaerobic digestion of the sewage sludge evaluated (‘control’: 47% biodegradable, 250 mL CH4/g VSfed) by increasing its BD and methane potential for all the conditions tested.

When correlating the main parameters with respect to the severity factor (Figure 4), some interesting behaviors can be observed.

Figure 4

Relationship between the different performance parameters and the severity factor (log R0).

Figure 4

Relationship between the different performance parameters and the severity factor (log R0).

First, the SF increased linearly with the severity as a direct consequence of the cell disruption that takes place during the thermal pretreatment (Dwyer et al. 2008), obtaining a solubilization of 40% of the particulate matter at the highest severity factor evaluated (log R0 = 4.1 in TH-14&15). The same results were obtained for the DF (maximum 40% degradation of the particulate matter in TH-14&15), thus meaning that all the organic matter solubilized was degraded to methane. Correspondingly, the BD increased linearly, from 47 to 64% at 180 °C–50 min pretreatment (TH-14). This linear link between COD solubilization and methane production is consistent with the results obtained by Carrère et al. (2008).

The lag phase increased dramatically from λ = 0 in the fresh control up to 3.5 days for severity log R0 > 3 (180 °C, t > 30 min), as previously presented in Figure 1(c)). It is generally considered that the extreme thermal hydrolysis conditions could lead to producing some slowly biodegradable or non-biodegradable recalcitrant compounds (in most TH cases melanoidins), making slower the multiplication of necessary bacteria and decreasing soluble phase consumption (Dwyer et al. 2008; Ariunbaatar et al. 2014).

When comparing the improvement in the methane production (mL CH4/g VSfed) and in the production rate (mL CH4/gVSfed.d), it can be observed that although the methane production increased with the severity (as previously commented), the methane production rate did not show the same trend, and exhibited an optimum at a severity factor of 3, then decreasing sharply, again pointing to the fact that the most severe pretreatment could lead to the formation of recalcitrant compounds.

An analysis of variance (ANOVA) was done for methane production in order to test the model significance and suitability. The significance of each coefficient was determined using the F-value test, at a 95% confidence level.

The results of the variance analysis are presented in Table 6. From there it can be concluded that coefficient for the linear effect of the temperature (A) on methane production is a statistically significant model term at 95% confidence level (P < 0.05), thus confirming that only temperature affected the increment of methane production.

Table 6

ANOVA table for the methane production of WAS using TH

Source Sum of squares DF Mean square F-value P-value 
A: Temperature 1,953.13 1,953.13 48.91 0.0001 
B: Time 78.125 78.125 1.96 0.1995 
C: Flash 50.0 50.0 1.25 0.2956 
AB 100.0 100.0 2.50 0.1522 
BB 123.626 123.626 3.10 0.1165 
CC 74.5728 74.5728 1.87 0.2089 
Error total 319.481 39.9351   
Total (corr.) 2,713.73 14    
Source Sum of squares DF Mean square F-value P-value 
A: Temperature 1,953.13 1,953.13 48.91 0.0001 
B: Time 78.125 78.125 1.96 0.1995 
C: Flash 50.0 50.0 1.25 0.2956 
AB 100.0 100.0 2.50 0.1522 
BB 123.626 123.626 3.10 0.1165 
CC 74.5728 74.5728 1.87 0.2089 
Error total 319.481 39.9351   
Total (corr.) 2,713.73 14    

Critical value (F0) for the F-test: 5.32 (F0.05, 1,8).

Although neither linear effects of the time (B) nor of the flash (C) on the methane production are statistically significant, the linear effect of the time (B) on methane production is more valid than the linear effect of the flash (C).

Based on the model, a maximum methane production 345 mL CH4/g VS (40% increase) was predicted at conditions: 180 °C, 45 min and 1 flash, with a desirability of 0.882.

CONCLUSIONS

This paper assesses through BMP tests of the influence of different temperature–time–flash thermal hydrolysis pretreatment conditions and combinations on the anaerobic degradation of secondary sludge. All the conditions tested (110–180 °C, 10–50 min, 1–3 flashes) presented higher methane production, exhibiting a maximum improvement of 40% solubilization and subsequent degradation of the particulate matter. Generally, the correlation between the severity of the pretreatment and the performance of the subsequent digestion was linear. However, only temperature showed a positive influence on the methane production, although at extreme thermal hydrolysis conditions, the lag phase increased dramatically, probably due to the formation of recalcitrant compounds. Time and re-flashing exhibited no significant influence.

REFERENCES

REFERENCES
Angelidaki
I.
Alves
M.
Bolzonella
D.
Borzacconi
L.
Campos
J. L.
Guwy
A. J.
Kalyuzhnyi
S.
Jenicek
P.
Van Lier
J. B.
2009
Defining the biomethane potential (BMP) of solid organic wastes and energy crops: a proposed protocol for batch assays
.
Water Science and Technology
59
(
5
),
927
934
.
Eaton
A. D.
Clesceri
L. S.
Greenberg
A. E.
2005
Standard Methods for the Examination of Water and Wastewater
,
21st edn
.
American Public Health Association/American Water Works Association/Water Environment 633 Federation,
Washington, DC
.
Ariunbaatar
J.
Panico
A.
Esposito
G.
Pirozzi
F.
Lens
P. N. L.
2014
Pretreatment methods to enhance anaerobic digestion of organic solid
.
Applied Energy
123
,
143
156
.
Cano Herranz
R.
2014
Pretreatment Technologies to Enhance Solid Wastes Anaerobic Digestion
.
PhD thesis
,
Department of Chemical Engineering and Environmental Technology, University of Valladolid
,
Spain
.
Carrère
H.
Bougrier
C.
Castets
D.
Delgenes
J. P.
2008
Impact of initial biodegradability on sludge anaerobic digestion enhancement by thermal pretreatment
.
Journal of Environmental Science and Health. Part A, Toxic/hazardous Substances & Environmental Engineering
43
(
13
),
1551
1555
.
Carrère
H.
Dumas
C.
Battimelli
A.
Batstone
D.
Delgenes
J.
Steyer
J.
Ferrer
I.
2010
Pretreatment methods to improve sludge anaerobic degradability: a review
.
Journal of Hazardous Materials
183
,
1
15
.
Donoso-Bravo
A.
Pérez-Elvira
S. I.
Fdz-Polanco
F.
2010
Application of simplified models for anaerobic biodegradability tests
.
Evaluation of pre-treatment processes
. Chemical Engineering Journal
160
(
2
),
607
614
.
Fernández-Polanco
F.
Velázquez
R.
Pérez-Elvira
S. I.
Casas
C.
Del Barrio
D.
Cantero
F. J.
Fernández-Polanco
M.
Rodríguez
P.
Panizo
L.
Serrat
J.
Rouge
P.
2008
Continuous thermal hydrolysis and energy integration in sludge anaerobic digestion plants
.
Water Science and Technology
57
(
8
),
1221
1226
.
Hii
K.
Baroutina
S.
Parthasarathy
R.
Gapes
D. J.
Eshtiaghi
N.
2014
A review of wet air oxidation and thermal hydrolysis technologies
.
Bioresource Technology
155
,
289
299
.
Lay
J. J.
Li
Y. Y.
Noike
T.
1997
Influences of pH and moisture content on the methane production in high-solids sludge digestion
.
Water Research
31
(
6
),
1518
1524
.
Nopharatana
A.
Pullammanappallil
P. C.
Clarke
W. P.
2007
Kinetics and dynamic modelling of batch anaerobic digestion of municipal solid waste in a stirred reactor
.
Waste Management
27
(
5
),
595
603
.
Oosterhuis
M.
Ringoot
D.
Hendriks
A.
Roeleveld
P.
2014
Thermal hydrolysis of waste activated sludge at Hengelo wastewater treatment plant, The Netherlands
.
Water Science and Technology
70
(
1
),
1
7
.
Pavlostathis
S. G.
Giraldo-Gomez
E.
1991
Kinetics of anaerobic treatment: A critical review
.
Critical Reviews in Environmental Control
21
(
5–6
),
411
490
.
Pérez-Elvira
S. I.
Fdz-Polanco
F.
Fdz-Polanco
M.
Rodríguez
P.
Rougé
P.
2008
Hydrothermal multivariable approach: full-scale feasibility study
.
Electronic Journal of Biotechnology
11
,
7
8
.
Redzwan
G.
Banks
C.
2004
The use of a specific function to estimate maximum methane production in a batch-fed anaerobic reactor
.
Journal of Chemical Technology and Biotechnology
79
(
10
),
1174
1178
.
Zhang
L.
Zhang
Y.
Zhang
Q.
Verpoort
F.
Cheng
W.
Caoi
L.
Li
M.
2014
Sludge gas production capabilities under various operational conditions of the sludge thermal hydrolysis pretreatment process
.
Journal of the Energy Institute
87
,
121
126
.