CET-vol 105


 

 DOI: 10.3303/CET23105037 
 

 
 
 
 
 
 

 
 
 

 
 

 

 
 

 
 
 

 
 
 

 
 
 

 
 
 

 
 
 

 
 

 
 
 

 

Paper Received: 14 February 2023; Revised: 6 April 2023; Accepted: 5 June 2023 
Please cite this article as: Rahma F.N., Li T., Khalil R., Tran K.-Q., 2023, Hydrothermal Gasification of Biogas Digestate: a Parametric 
Study Using a Matlab-based Code, Chemical Engineering Transactions, 105, 217-222  DOI:10.3303/CET23105037 

CHEMICAL ENGINEERING TRANSACTIONS 

VOL. 105, 2023 

A publication of 

The Italian Association 

of Chemical Engineering 

Online at www.cetjournal.it 

Guest Editors: David Bogle, Flavio Manenti, Piero Salatino 

Copyright © 2023, AIDIC Servizi S.r.l.

ISBN 979-12-81206-04-5; ISSN 2283-9216

Hydrothermal Gasification of Biogas Digestate: a Parametric 

Study using a Matlab-based Code 

In this work, effect of process parameters on hydrothermal gasification (HTG) of biogas digestate are 

thermodynamically investigated using a Matlab-based code, which is capable of modelling the effects of the 

feedstock’s inorganic contents and elements. The effects of temperature (400-600 oC), pressure (250-300 bar),

and feed concentration (10-40 wt%) towards the producer gas yield and composition are evaluated while

considering the influence of inorganic components in the feedstock. The result shows that temperature and feed 

concentration play significant roles in determining producer gas composition and yield, whereas pressure only 

has little influence. Hydrogen production is favored by higher temperature, lower pressure, and lower feed

concentration. It was also observed that the presence of inorganic components in the feedstock reduces the

production of CO2, while H2 and CH4 is increased. The result of this study is essential in the future development 

of biogas digestate HTG.

1. Introduction

In the recent years, the increasing urgency of combatting with climate change has been accelerating the energy

transition towards renewable and sustainable resources. Biogas produced from low-grade biomass materials 

via anaerobic digestion is an important alternative in this transition, mainly due to its flexibility to be used as

transport fuel, heat, and electricity sources (Scarlat, Dallemand et al. 2018). However, the biogas technology

still faces significant issues associated with complicated treatment and management of digestate (Nkoa 2014,

Guilayn, Rouez et al. 2020), as well as insufficient supply of sustainable feedstock (Divya, Gopinath et al. 2015). 

A potential solution to overcome both problems is by integrating anaerobic digestion (AD) with hydrothermal 

gasification (HTG). In such an integrated system, wet digestate produced from the AD unit can be gasified, with

no need of drying, in the HTG unit to reduce the load of digestate management and to recover the energy

content remaining in the digestate. This integration can also widen the AD feedstock choices to include 

lignocellulosic biomass, which normally is not very suitable as AD feedstock due to their composition and 

structure complexity (Sudibyo, Pecchi et al. 2022). On the other hand, the producer gas generated from the 

HTG unit can be recycled back to the AD for enhancing the biogas production (Yang, Liu et al. 2020). 

The implementation of AD-HTG integration with producer gas recycling requires a comprehensive 

understanding about the impact of process parameters on HTG performance including the yield and composition 

of the producer gas. Past parametric studies on HTG and producer gas using thermodynamic modelling 

approach have been quite active, of which several focused on investigating the effect of different types of

biomass feedstock (Freitas and Guirardello 2013, Macrì, Catizzone et al. 2020, Okolie, Epelle et al. 2021). 

However, to the best of the authors’ knowledge, the use of biogas digestate as HTG feedstock has not been 

studied. More importantly, attempt to investigate the effect of inorganic components of the feedstock on HTG

performance was very limited, while it has been reported that the inorganic components of the feedstock could 

cause significant differences between modelling and experimental data (Mutlu and Zeng 2020). This suggests

the importance of considering the feedstock’s inorganic components and their chemistry in HTG modelling. 

217

Fadilla N. Rahmaa,*, Tian Lia, Roger Khalilb, Khanh-Quang Trana 
aDepartment of Energy and Process Engineering, Norwegian University of Science and Technology (NTNU), Norway 
bSINTEF Energy Research, Norway  
 fadilla.n.rahma@ntnu.no 



The present research aims to investigate into parametric effects on HTG performance and the behavior of 

producer gas from the HTG of biogas digestate while taking into account the effect of feedstock’s inorganic 

components. For this purpose, a multiphase thermodynamic model developed in Matlab by Yakaboylu et al. 

(Yakaboylu, Harinck et al. 2014), which is capable of predicting compound formation over a wider range of 

feedstock types as well as using more updated thermodynamic data for the solute species, will be employed. 

The effect of key process parameters such as temperature, pressure, and feedstock dry matter content on the 

producer gas composition and yield is evaluated. This work would serve as a foundation for future development 

of an integrated AD-HTG system, considering the effect of inorganic components of the feedstock.  

2. Methods

2.1 Model Description 

As aforementioned, the present study is carried out, employing the multiphase thermodynamic model developed 

by Yakaboylu et al. The model has been validated with experimental data. Full description of the model can be 

found in the literature (Yakaboylu, Harinck et al. 2014). A non-stoichiometric approach based on Gibbs free 

energy minimization is adopted in the model. For a given temperature and pressure, the model predicts product 

composition at the system’s equilibrium state, which is reached when the Gibbs free energy is at minimum with 

respect to all possible changes. The equilibrium state is mathematically defined in Equation (1). 

(𝑑G𝑡)𝑇,𝑃 = 0 (1) 

The model is capable of predicting phase distribution of product components by performing multiphase 

thermodynamic calculations, considering both organic and inorganic components in the feedstock. In a 

multiphase system, the total Gibbs free energy is calculated as the sum of Gibbs free energy from each phase. 

Hence, in this thermodynamic model, the Gibbs free energy calculation is carried out for three phases included 

in the system, namely 1) gas phase, 2) pure condensed phases, and 3) aqueous solution phases. The total 

Gibbs free energy is presented in Equation (2), where the subscripts i and w refers to component i and water, 

respectively. The terms 𝑛, 𝜇, 𝑔𝑜, 𝑥, and 𝛾 respectively represent the component mole amount, the gas chemical 

potential, the component’s standard molar Gibbs free energy, the component mole fraction, and the activity 

coefficient based on the component mole fraction. 

𝐺 = ∑ 𝑛𝑖𝜇𝑖
gas

phase

+ ∑ 𝑛𝑖
pure

condensed
phases

𝑔𝑖
𝑜 + 𝑛𝑤(𝑔𝑤

𝑜 + 𝑅𝑇 ln 𝑥𝑤 + 𝑅𝑇 ln 𝛾𝑤)

+ ∑ 𝑛𝑖
aqueous
solution

(𝑔𝑖
𝑜 + 𝑅𝑇 ln 𝑥𝑖 + 𝑅𝑇 ln 𝛾𝑖)

(2) 

2.1.1. Calculations for the gas phase 

The Gibbs free energy for gas phase is defined as the first term in Equation (2). As the supercritical condition of 

the HTG system leads to a non-ideal behavior of the gas, the Gibbs free energy calculation is based on the 

chemical potential of the gases. The gas phase calculation employs Peng-Robinson equation of state (EoS) 

with thermodynamic data acquired from the FACT53 database of the FactSage software.  

2.1.2. Calculations for the pure condensed phase 

The second term in Equation (2) represents the Gibbs free energy of the pure condensed phases. The required 

thermodynamic data for the pure condensed phases was also obtained from the FACT53 database of the 

FactSage software. 

2.1.3. Calculations for the aqueous solution 

In Equation (2), the Gibbs free energy of the aqueous solution is represented by the third term for the calculation 

of water in the aqueous phase, and the last term for the solute species. The thermodynamic data for the solute 

species were taken from the SUPCRT92 software. For the supercritical region, where the water in the aqueous 

phase is completely vaporized, the calculation is based on an assumption that the solute molecules interact with 

gases to form aqueous hydrate complexes (Chrastil 1982).   

The thermodynamic model is implemented in Matlab using fmincon routine to minimize Equation (2) and obtain 

the amounts of species at the equilibrium state. A mole and charge balance constraint and non-negativity 

species amount constraint are applied during the minimization. The required inputs are process conditions, i.e., 

temperature and pressure, and the molar composition of feedstock and water. The feedstock composition is 

taken from biogas digestate data available on literature (Parmar and Ross 2019). 

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Table 1: Proximate Analysis of Feedstock Materials (Parmar and Ross 2019) 

Proximate Analysis (wt%) Value (db) 

Fixed Carbon 8.3 

Volatile Matters 36.2 

Ash 55.5 

Table 2. Ultimate Analysis of Feedstock Materials (Parmar and Ross 2019) 

Ultimate Analysis (wt%) Value (db) 

C 24.1 

H 1.7 

O 16.9 

N 1.5 

S 0.2 

Ca 10.4 

Cl 0.0 

K 1.6 

Mg 1.4 

Na 0.9 

P 0.7 

Si 10.2 

2.2 Chemical Reactions in Hydrothermal Gasification 

Hydrothermal gasification of biomass includes a series of chemical reactions which produces H2, CO, CO2, and 

CH4 as the main components in the gaseous phase. The steam reforming reaction (Equation 3), water gas shift 

reaction (WGSR) (Equation 4), and methanation reaction (Equation 5) are commonly considered as the main 

chemical reactions in HTG (Xu, Peng et al. 2021, Yang, Wang et al. 2021). The steam reforming reaction 

produces CO and H2 from endothermic decomposition of biomass. The reversible WGSR produces more H2 

and CO2 through exothermic reaction of CO and H2O. On the other hand, the reversible methanation reaction 

consumes H2 to react with CO, producing CH4 and H2O (Yang, Wang et al. 2021).  

CHxOy + (1 − y)H2O → CO + (1 +
x

2
− y) H2 (3) 

CO + H2O ↔ CO2 + H2      ∆H(25 ℃) = −41.14 kJ/mol (4) 

CO + 3H2 ↔ CH4 + H2O   ∆H(25 ℃) = −205.89 kJ/mol (5) 

3. Results and Discussion

3.1 Effect of Temperature 

Figure 1 (a) shows the effect of temperature towards the producer gas composition at different weight 

percentages of inorganic components. The temperature influence observed in this figure agrees well with 

previous studies (Tang and Kitagawa 2005, Voll, Rossi et al. 2009). Higher temperature enhances hydrogen 

production by promoting the endothermic steam reforming reaction (Equation 3). As the temperature increases, 

the methanation reaction (Equation 5) is also reversed, therefore CH4 is consumed to produce more H2. This 

also explains the decrease in methane production at higher temperature. The production of CO2 is favored at 

lower temperatures, although the temperature dependence is less significant since WGSR is only slightly 

exothermic. The amount of CO is negligible at the investigated temperature range, indicating that CO is almost 

completely consumed in the WGSR and methanation reaction. On the other hand, Figure 1 (b) shows that the 

total gas yield is positively influenced by temperature. This result is in agreement with the literature, concerning 

with HTG of other biomass feedstocks (Voll, Rossi et al. 2009, Freitas and Guirardello 2014).  

In addition, both figures also demonstrate the effect of inorganic contents on the producer gas yield and 

composition. For any temperature within the observed range, a higher inorganic content always leads to a lower 

production of CO2. This might be due to the formation of inorganic salts such as CaCO3, Na2CO3, and K2CO3 

from the reactions between inorganic components and CO2. As a consequence of the lower CO2 composition, 

the WGSR is driven towards the forward direction to produce more H2. This explains the higher H2 composition 

at higher inorganic content. The result is consistent with the experimental observation reported by Guo et al. 

219



(Guo, Guo et al. 2012) and Xu et al (Xu, Wang et al. 2009). Furthermore, Onwudili et al. (Onwudili and Williams 

2014) argued that the presence of alkali metals promotes hydrogen production by accelerating the WGSR 

through the removal of CO2 as carbonate. Su et al. (Su, Yan et al. 2022) also reported that the production of 

potassium salts improves the WGSR, resulting in higher H2 production. The increased H2 amount due to higher 

inorganic contents also enhances the production of CH4 through the methanation reaction. Furthermore, Figure 

1 (a) shows that the effect of inorganic contents on gas composition is more prominent at lower temperatures. 

This might be due to the decreasing carbonate salts forming reaction at higher temperature, which is consistent 

with the simulation result, although not presented in this paper.  

(a) (b) 

Figure 1. The effect of temperature on producer gas (a) composition and (b) yield at different inorganic contents 

(P = 280 bar, feedstock concentration = 10%, inorganic contents = 100%, 50%, and 0% wt.) 

The effect of inorganic contents on the total gas yield is presented in Figure 1 (b). The figure indicates that at 

lower temperature, higher inorganic contents are associated with lower gas yields. The trend is reversed at 

higher temperatures, where a higher gas yields are obtained for the feedstock with higher inorganic contents. 

3.2 Effect of Pressure 

Figure 2 (a) and (b) demonstrate how pressure influences the producer gas composition and yield. It is observed 

that pressure gives minor effect on both gas composition and yield. However, a slight decrease in H2 production 

and increase in CH4 formation is observed at higher pressures. According to the Le Chatelier principle, higher 

HTG pressure promotes the methanation reaction (Equation 5), hence more CH4 is produced from H2.  This 

result agrees well with findings from previous studies (Castello and Fiori 2011, Hantoko, Su et al. 2018). 

The effect of different inorganic contents of the feedstock is also displayed in both figures. Consistent trends 

similar to what presented in the previous section are also observed. Higher inorganic contents negatively affect 

CO2 formation, however, the production of both H2 and CH4 is increased. The increase in H2 and CH4 production 

is more significant than the decrease in CO2. Overall, the total gas yield increases for higher inorganic contents, 

as indicated by Figure 2 (b).  

(a) (b) 

Figure 2. The effect of pressure on producer gas (a) composition and (b) yield at different inorganic contents (T 

= 600 oC, feedstock concentration = 10%, inorganic contents = 100%, 50%, and 0% wt.) 

3.3 Effect of Feed Concentration 

The effect of feed concentration on gas composition and yield is presented on Figure 3 (a) and (b), respectively. 

Note that, for this investigation, the total mass of feed and water was kept constant during the simulation. 

Therefore, a higher feed concentration represents a higher amount of feed and lower amount of water. In an 

HTG system, water acts as a reactant which can significantly influence the chemical reactions. Figure 3 (a) 

indicates that H2 composition is significantly reduced at higher feed concentration. This is because the 

decreasing water amount affects the methanation reaction, pushing it towards the direction of CH4 production 

220



from H2. This is also consistent with the significant increase in CH4 composition at higher feed concentration. 

On the other hand, Figure 3 (b) indicates that the overall gas yield decreases notably at higher feed 

concentration. Similar findings were previously published in an earlier study (Hantoko, Su et al. 2018). 

Both Figure 3 (a) and (b) also demonstrate the effect of inorganic contents on the producer gas yield and 

composition. Similar with the result presented in the previous sections, a higher inorganic content always leads 

to a decrease in CO2 composition and increase in H2 and CH4 composition. According to the simulation result, 

the formation of carbonate salts is promoted at higher feed composition. Consequently, the effect of inorganic 

contents on gas composition is more prominent when the feed composition is higher.  

(a) (b) 

Figure 3. The effect of feedstock concentration on producer gas (a) composition and (b) yield at different 

inorganic contents (T = 600 oC, P = 280 bar, inorganic contents = 100%, 50%, and 0% wt.) 

4. Conclusions

The present work investigated the influence of important process parameters in the HTG of biogas digestate 

such as temperature, pressure, and feed concentration, while taking into account the effect of inorganic contents 

in the feedstock. The study found that temperature rise increases H2 composition and decreases CH4 

composition, while CO2 composition is only slightly affected. Temperature also positively influences the total 

gas yield. Pressure has less significant effect, however, a slight increase in total gas yield and CH4 composition 

and a slight decrease in H2 composition is observed at higher pressure. A higher feed concentration significantly 

increases the production of CH4, while H2 composition, and overall gas yield decrease. Furthermore, it was 

observed that higher inorganic contents lead to a lower CO2 composition, while H2 and CH4 composition are 

increased. These results provide a novel insight on a thermodynamic model’s behavior when the feedstock 

inorganic content is considered.  

Acknowledgement 

This work was supported by the BioSynGas project partly funded by the Research Council of Norway (Project 
Number: 319723). The authors also want to thank Onursal Yakaboylu for developing the Matlab model used in 
this study, and for his valuable inputs and discussions

References 

Castello, D. and L. Fiori (2011). "Supercritical water gasification of biomass: Thermodynamic constraints." 

Bioresource technology 102(16): 7574-7582. 

Chrastil, J. (1982). "Solubility of solids and liquids in supercritical gases." The Journal of Physical Chemistry 

86(15): 3016-3021. 

Divya, D., L. Gopinath and P. M. Christy (2015). "A review on current aspects and diverse prospects for 

enhancing biogas production in sustainable means." Renewable and sustainable energy reviews 42: 

690-699. 

Freitas, A. and R. Guirardello (2013). "Thermodynamic analysis of supercritical water gasification of microalgae 

biomass for hydrogen and syngas production." Chemical Engineering Transactions 32: 553-558. 

Freitas, A. C. and R. Guirardello (2014). "Comparison of several glycerol reforming methods for hydrogen and 

syngas production using Gibbs energy minimization." International journal of hydrogen energy 39(31): 

17969-17984. 

Guilayn, F., M. Rouez, M. Crest, D. Patureau and J. Jimenez (2020). "Valorization of digestates from urban or 

centralized biogas plants: a critical review." Reviews in Environmental Science and Bio/Technology 19(2): 

419-462.

Guo, S., L. Guo, C. Cao, J. Yin, Y. Lu and X. Zhang (2012). "Hydrogen production from glycerol by supercritical 

water gasification in a continuous flow tubular reactor." International Journal of Hydrogen Energy 37(7): 

5559-5568. 

221



Hantoko, D., H. Su, M. Yan, E. Kanchanatip, H. Susanto, G. Wang, S. Zhang and Z. Xu (2018). "Thermodynamic 

study on the integrated supercritical water gasification with reforming process for hydrogen production: 

Effects of operating parameters." International Journal of Hydrogen Energy 43(37): 17620-17632. 

Macrì, D., E. Catizzone, A. Molino and M. Migliori (2020). "Supercritical water gasification of biomass and agro-

food residues: Energy assessment from modelling approach." Renewable Energy 150: 624-636. 

Mutlu, Ö. Ç. and T. Zeng (2020). "Challenges and opportunities of modeling biomass gasification in Aspen Plus: 

A review." Chemical Engineering & Technology 43(9): 1674-1689. 

Nkoa, R. (2014). "Agricultural benefits and environmental risks of soil fertilization with anaerobic digestates: a 

review." Agronomy for Sustainable Development 34(2): 473-492. 

Okolie, J. A., E. I. Epelle, S. Nanda, D. Castello, A. K. Dalai and J. A. Kozinski (2021). "Modeling and process 

optimization of hydrothermal gasification for hydrogen production: A comprehensive review." The Journal of 

Supercritical Fluids 173: 105199. 

Onwudili, J. A. and P. T. Williams (2014). Production of hydrogen from biomass via supercritical water 

gasification. Near-critical and supercritical water and their applications for biorefineries, Springer: 299-322. 

Parmar, K. R. and A. B. Ross (2019). "Integration of hydrothermal carbonisation with anaerobic digestion; 

Opportunities for valorisation of digestate." Energies 12(9): 1586. 

Scarlat, N., J.-F. Dallemand and F. Fahl (2018). "Biogas: Developments and perspectives in Europe." 

Renewable energy 129: 457-472. 

Su, H., M. Yan and S. Wang (2022). "Recent advances in supercritical water gasification of biowaste catalyzed 

by transition metal-based catalysts for hydrogen production." Renewable and Sustainable Energy Reviews 

154: 111831. 

Sudibyo, H., M. Pecchi and J. W. Tester (2022). "Experimental-based mechanistic study and optimization of 

hydrothermal liquefaction of anaerobic digestates." Sustainable Energy & Fuels 6(9): 2314-2329. 

Tang, H. and K. Kitagawa (2005). "Supercritical water gasification of biomass: thermodynamic analysis with 

direct Gibbs free energy minimization." Chemical Engineering Journal 106(3): 261-267. 

Voll, F., C. Rossi, C. Silva, R. Guirardello, R. Souza, V. Cabral and L. Cardozo-Filho (2009). "Thermodynamic 

analysis of supercritical water gasification of methanol, ethanol, glycerol, glucose and cellulose." 

International Journal of Hydrogen Energy 34(24): 9737-9744. 

Xu, D., S. Wang, X. Hu, C. Chen, Q. Zhang and Y. Gong (2009). "Catalytic gasification of glycine and glycerol 

in supercritical water." International journal of hydrogen energy 34(13): 5357-5364. 

Xu, J., Z. Peng, S. Rong, H. Jin, L. Guo, X. Zhang and T. Zhou (2021). "Model-based thermodynamic analysis 

of supercritical water gasification of oil-containing wastewater." Fuel 306: 121767. 

Yakaboylu, O., J. Harinck, K. Smit and W. de Jong (2014). "Supercritical water gasification of biomass: A 

thermodynamic model for the prediction of product compounds at equilibrium state." Energy & fuels 28(4): 

2506-2522. 

Yang, C., S. Wang, Y. Li, Y. Zhang and C. Cui (2021). "Thermodynamic analysis of hydrogen production via 

supercritical water gasification of coal, sewage sludge, microalga, and sawdust." International Journal of 

Hydrogen Energy 46(34): 18042-18050. 

Yang, Z., Y. Liu, J. Zhang, K. Mao, M. Kurbonova, G. Liu, R. Zhang and W. Wang (2020). "Improvement of 

biofuel recovery from food waste by integration of anaerobic digestion, digestate pyrolysis and syngas 

biomethanation under mesophilic and thermophilic conditions." Journal of Cleaner Production 256: 120594. 

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	Hydrothermal Gasification of Biogas Digestate: a Parametric Study using a Matlab-based Code