DOI: 10.3303/CET24114104 Paper Received: 4 July 2024; Revised: 17 October 2024; Accepted: 20 November 2024 Please cite this article as: Zebian B., Bouallou C., 2024, Modelling of Biomethane Production from Microalgae, Chemical Engineering Transactions, 114, 619-624 DOI:10.3303/CET24114104 CHEMICAL ENGINEERING TRANSACTIONS VOL. 114, 2024 A publication of The Italian Association of Chemical Engineering Online at www.cetjournal.it Guest Editors: Petar S. Varbanov, Min Zeng, Yee Van Fan, Xuechao Wang Copyright Β© 2024, AIDIC Servizi S.r.l. ISBN 979-12-81206-12-0; ISSN 2283-9216 Microalgae are a prospective feedstock for bioenergy due to their higher productivity, adaptable growing environments, and higher lipid/polysaccharide content compared to terrestrial biomass. Anaerobic digestion is a well-established process that can turn microalgae into biogas and offers a high energy return on investment. The ADM1 model, coupled with a pre-treatment step and a full upgrading processing of the biogas, was implemented. Aspen Plus was the software used to display the process of converting biomass to biomethane through anaerobic digestion and biogas purification techniques in order to determine the mass balance and energy requirements. Simulations were compared to experimental data obtained from University of Almeria, Spain of an anaerobic digester fed with Scenedesmus microalgae. For a 5-ha wastewater open raceway pond and a biomass productivity of 20 g/m2/day, the biomethane had a purity of 94 % using anaerobic digestion accompanied with an enzymatic pre-treatment and amine scrubbing for biogas purification. 1. Introduction The world is currently having a difficult time keeping up with the rising demand for energy, driven by population growth, urbanization, and industrialization. Fossil fuels have historically been the main source of energy, but their finite supply, growing costs, and detrimental impacts on the environment have driven a shift towards alternative sources of energy (IEA, 2024). Renewable energy is becoming more and more competitive with fossil fuels thanks to economies of scale as well as research and development initiatives. In the context of ambitions to reach net-zero emissions, one of the most attractive biofuels is biogas that may be generated from a variety of terrestrial, renewable bio-based feedstocks. If managed sustainably, it can contribute to the reduction of greenhouse gas emissions and air pollution while serving as a sustainable and renewable source of energy for heat, power, and transportation (Ayala-Parra et al., 2017). Most of this gas is methane (CH4) and carbon dioxide (CO2) which can be used for a variety of purposes, including the production of heat and electricity, liquefaction into methanol, compression into vehicle fuel, and purification into pipeline gas (IEA, 2020). As such, the share of biogas used for power and heat will rise to 85 % by 2040 (IEA, 2020). The production and conversion of these feedstocks could come, however, with concerns related to eutrophication, freshwater resource depletion, food chain disruption, and biodiversity loss. The focus on microalgal biogas production has been heightened to address the drawbacks of first- and second-generation biofuels because it has been determined that such traditional biomass is not completely carbon neutral (Gerado et al., 2015). Microalgae, a prospective feedstock, has numerous benefits over terrestrial plants, including a rapid rate of growth, the capacity to use atmospheric CO2, and the ability to be grown on non-arable areas using wastewater as a growth medium (Cavinato et al., 2017). Biogas can be obtained from harvested microalgae biomass by a traditional and naturally occurring biological process, namely anaerobic digestion (AD). In AD, several bacterial and archaeal species interact in an oxygen-free environment to biodegrade organic materials into biogas. This method recovers the stored energy from biomass and releases ammonium and phosphate, which can in turn be used as nutrients for microalgae cultivation. Therefore, combining microalgae cultivation with anaerobic digestion offers a viable way to convert solar energy into methane. After AD, the produced biogas 619 Modelling of Biomethane Production from Microalgae Bashar Zebian*, Chakib Bouallou MINES Paris, UniversitΓ© PSL, Centre Energie Environnement ProcΓ©dΓ©s (CEEP), 75272 Paris, France bashar.zebian@etu.minesparis.psl.eu largely consists of CH4 (55-70 %) and CO2 (30-45 %), as well as trace amounts of H2S (50-2000 ppm), H2O, and H2 (Harun et al., 2018). The aim of this work was to develop a simulation model of microalgal biogas using Aspen Plus software and life cycle thinking as the methodological framework. This integrated method promotes decision-making and optimization of the process ensuring it is scalable and efficient while determining the essential information to model a precise replica of the desired process. Its significance lies in the potential of microalgae as a sustainable energy source, contributing to the reduction of fossil fuel dependence. As a result, the required mass and energy inputs were estimated using mass and energy balances and based on experimental data from the University of Almeria and Aspen plus software for the AD stage to identify upscaled scenarios, a working flowsheet was built in a way that it would be consistent with the actual data collected. 2. Modes and Materials This work explores a cultivation baseline scenario using wastewater in pilot open raceway ponds at University of Almeria for microalgae growth, eliminating the need for additional nutrients. The process begins with the installation of infrastructure, followed by cultivation in open raceway pond, where wastewater and CO2 are continuously stirred, compensating for water loss due to evaporation. Harvesting occurs through single-stage membrane filtration, and the permeate is discharged safely. AD involves four steps as shown in Figure 1: enzymatic pre-treatment to break down cell walls, digestion in a CSTR to produce biogas, upgrading the biogas to biomethane via amino chemical washing, and valorising the digestate by separating it into solid and liquid components for potential fertilizer use and nutrient recycling. Figure 1: Biomethane Production Flowsheet 2.1 Simulation Model Most industrial companies are concentrating on process simulation modelling since it is a method to reduce time and financial investments and accurately replicates plant operations. Aspen Plus software was used to model the desired anaerobic digestion process of microalgae and the upgrading part of the biogas. The first step in the simulation procedure is choosing the property package, in this case NRTL (non-random, two liquid model) was chosen due to its capability to compute activity coefficients and mole fractions, includes vapor and liquid phases, and incorporates polar substrate components. Anaerobic digestion kinetics can be described by a variety of models. Some of these models concentrate on the process's inhibitors, whilst other models describe the AD process. The most fundamental model for AD is known as Anaerobic Digestion Model No. 1 (ADM1) which provides the reaction kinetics of the anaerobic digestion stages and of the temperature. 2.1.1 Scope of application of the model The developed model for anaerobic digestion and biogas upgrading using ASPEN Plus is versatile and applicable to various scales of biogas production facilities. This flexibility makes it suitable for both small pilot plants and large industrial setups that aids in the design, optimization, and operation of AD systems. It contributes also significantly to the advancement of sustainable biogas production technologies and lays the groundwork for evaluating the economic feasibility of this process. 2.1.2 Microalgae composition ADM1 model assumes that the substrate fed into the system as a feed will be composed of proteins, carbohydrates, lipids, and inerts. In the case of microalgae, carbohydrates were incorporated as (𝐢6𝐻12𝑂6)𝑛, lipids as triolein (𝐢57𝐻104𝑂6), and proteins as (𝐢4.7𝐻8.7𝑂2.2𝑁1.24𝑆0.02). 620 For the case of proteins, the formula was found based on the amino acid profile of the cultivated microalgae. Table 1 summarizes the microalgae composition which will be introduced as the feedstock in the Aspen model. Table 1: Microalgae composition Raw Scenedesmus (wastewater) Mean SD pH 6.4 Β± 0.1 N-NH4+ (mg/L) 141.2 Β± 3.7 C/N 6.3 Β± 0.1 TCOD (g/L) 27.6 Β± 2.1 TS (g/L) 16.8 Β± 1.4 VS (g/L) 15.2 Β± 1.0 Inert (%)* 9.1 Β± 0.6 Carbohydrates (%)* 18.1 Β± 1.6 Proteins (%)* 52.3 Β± 0.5 Lipids (%)* 20.5 Β± 1.1 *Percentage calculated based on dry matter content 2.1.3 Reaction list The precise reactions involved in the AD are added as following the power law of first order in which their kinetic constants are obtained from previous literature studies and showed in Table 2 (Rajendran et al., 2014). Table 2: Reaction list involved in the digestor Phase Number Compound Reaction Hydrolysis 1 Cellulose (𝐢6𝐻12𝑂6)𝑛 + 𝐻2𝑂 β†’ 𝑛 𝐢6𝐻12𝑂6 2 Cellulose 𝐢6𝐻12𝑂6 + 𝐻2𝑂 β†’ 2 𝐢2𝐻6𝑂 + 2𝐢𝑂2 3 Ethanol 2 𝐢2𝐻6𝑂 + 𝐢𝑂2 β†’ 2 𝐢2𝐻4𝑂2 + 𝐢𝐻4 4 Triolein 𝐢57𝐻104𝑂6 + 3 𝐻2𝑂 β†’ 𝐢3𝐻8𝑂3 + 3 𝐢18𝐻34𝑂2 5 Proteins Proteins + Water β†’ AA Amino Acid Degradation 1 Glycine 𝐢2𝐻5𝑁𝑂2 + 𝐻2 β†’ 𝐢2𝐻4𝑂2 + 𝑁𝐻3 2 Threonine 𝐢4𝐻9𝑁𝑂3 + 𝐻2 β†’ 𝐢2𝐻4𝑂2 + 0.5 𝐢4𝐻8𝑂2 + 𝑁𝐻3 3 Histidine 𝐢6𝐻8𝑁3𝑂2 + 4 𝐻2𝑂 + 0.5 𝐻2 β†’ 𝐢𝐻3𝑁𝑂 + 𝐢2𝐻4𝑂2 + 0.5 𝐢4𝐻8𝑂2 + 2 𝑁𝐻3 + 𝐢𝑂2 4 Arginine 𝐢6𝐻14𝑁4𝑂2 + 3 𝐻2𝑂 + 𝐻2 β†’ 0.5 𝐢3𝐻6𝑂2 + 0.5 𝐢2𝐻4𝑂2 + 0.5 𝐢5𝐻10𝑂2 + 4 𝑁𝐻3 + 𝐢𝑂2 5 Proline 𝐢5𝐻9𝑁𝑂2 + 𝐻2𝑂 + 𝐻2 β†’ 0.5 𝐢2𝐻4𝑂2 + 0.5 𝐢3𝐻6𝑂2 + 0.5 𝐢5𝐻10𝑂2 + 𝑁𝐻3 6 Methionine 𝐢5𝐻11𝑁𝑂2𝑆 + 2 𝐻2 β†’ 𝐢3𝐻6𝑂2 + 𝐻2 + 𝐢𝐻4𝑆 + 𝑁𝐻3 + 𝐢𝑂2 7 Serine 𝐢3𝐻7𝑁𝑂3 + 𝐻2𝑂 β†’ 𝐢2𝐻4𝑂2 + 𝑁𝐻3 + 𝐢𝑂2 + 𝐻2 8 Threonine 𝐢4𝐻9𝑁𝑂3 + 𝐻2𝑂 β†’ 𝐢3𝐻6𝑂2 + 𝑁𝐻3 + 𝐢𝑂2 + 𝐻2 9 Aspartic Acid 𝐢4𝐻7𝑁𝑂4 + 2 𝐻2𝑂 β†’ 𝐢2𝐻4𝑂2 + 𝑁𝐻3 + 2 𝐢𝑂2 + 2 𝐻2 10 Glutamic Acid 𝐢5𝐻9𝑁𝑂4 + 𝐻2𝑂 β†’ 𝐢2𝐻4𝑂2 + 0.5 𝐢4𝐻8𝑂2 + 𝑁𝐻3 + 𝐢𝑂2 11 Glutamic Acid 𝐢5𝐻9𝑁𝑂4 + 2 𝐻2𝑂 β†’ 2 𝐢2𝐻4𝑂2 + 𝑁𝐻3 + 𝐢𝑂2 + 𝐻2 12 Histidine 𝐢6𝐻8𝑁3𝑂2 + 4 𝐻2𝑂 + 0.5 𝐻2 β†’ 𝐢𝐻3𝑁𝑂 + 𝐢2𝐻4𝑂2 + 0.5 𝐢4𝐻8𝑂2 + 2 𝑁𝐻3 + 𝐢𝑂2 13 Arginine 𝐢6𝐻14𝑁4𝑂2 + 6 𝐻2𝑂 β†’ 2 𝐢2𝐻4𝑂2 + 3 𝐻2 + 4 𝑁𝐻3 + 2 𝐢𝑂2 14 Lysine 𝐢6𝐻14𝑁2𝑂2 + 2 𝐻2𝑂 β†’ 𝐢2𝐻4𝑂2 + 𝐢4𝐻8𝑂2 + 2 𝑁𝐻3 15 Leucine 𝐢6𝐻13𝑁𝑂2 + 2 𝐻2𝑂 β†’ 𝐢5𝐻10𝑂2 + 𝑁𝐻3 + 𝐢𝑂2 + 2 𝐻2 16 Isoleucine 𝐢6𝐻13𝑁𝑂2 + 2 𝐻2𝑂 β†’ 𝐢5𝐻10𝑂2 + 𝑁𝐻3 + 𝐢𝑂2 + 2 𝐻2 17 Valine 𝐢5𝐻11𝑁𝑂2 + 2 𝐻2𝑂 β†’ 𝐢4𝐻8𝑂2 + 𝑁𝐻3 + 𝐢𝑂2 + 2 𝐻2 18 Phenyalanine 𝐢9𝐻11𝑁𝑂2 + 2 𝐻2𝑂 β†’ 𝐢6𝐻6 + 𝐢2𝐻4𝑂2 + 𝑁𝐻3 + 𝐢𝑂2 + 𝐻2 19 Tyrosine 𝐢9𝐻11𝑁𝑂3 + 2 𝐻2 β†’ 𝐢6𝐻6𝑂 + 𝐢2𝐻4𝑂2 + 𝑁𝐻3 + 𝐢𝑂2 + 𝐻2 20 Glycine 𝐢2𝐻5𝑁𝑂2 + 0.5 𝐻2𝑂 β†’ 0.75 𝐢2𝐻4𝑂2 + 𝑁𝐻3 + 0.5 𝐢𝑂2 21 Alanine 𝐢3𝐻7𝑁𝑂2 + 2 𝐻2𝑂 β†’ 𝐢2𝐻4𝑂2 + 𝑁𝐻3 + 𝐢𝑂2 + 2 𝐻2 22 Cysteine 𝐢3𝐻6𝑁𝑂2𝑆 + 2 𝐻2 β†’ 𝐢2𝐻4𝑂2 + 𝑁𝐻3 + 𝐢𝑂2 + 0.5 𝐻2 + 𝐻2𝑆 Acidogenesis 1 Dextrose 𝐢6𝐻12𝑂6 + 0.1115 𝑁𝐻3 β†’ 0.1115 𝐢5𝐻7𝑁𝑂2 + 0.744 𝐢2𝐻4𝑂2 + 0.5 𝐢3𝐻6𝑂2 +0.4409 𝐢4𝐻8𝑂2 + 0.6909 𝐢𝑂2 + 1.0254 𝐻2𝑂 2 Glycerol 𝐢3𝐻8𝑂3 + 0.04071 𝑁𝐻3 + 0.0291 𝐢𝑂2 + 0.00005 𝐻2 β†’ 0.04071 𝐢5𝐻7𝑁𝑂2 + 0.94185 𝐢3𝐻6𝑂2 + 1.093 𝐻2𝑂 621 Table 2: Reaction list involved in the digestor (Continued) Phase Number Compound Reaction Acetogenesis 1 Oleic Acid 𝐢18𝐻34𝑂2 + 15.2396 𝐻2𝑂 + 0.2501 𝐢𝑂2 + 0.1701 𝑁𝐻3 β†’ 0.1701 𝐢5𝐻7𝑁𝑂2 + 8.6998 𝐢2𝐻4𝑂2 + 14.4978 𝐻2 2 Propionic Acid 𝐢3𝐻6𝑂2 + 0.314336 𝐻2𝑂 + 0.06198 𝑁𝐻3 β†’ 0.06198 𝐢5𝐻7𝑁𝑂2 + 0.9345 𝐢2𝐻4𝑂2 +0.660412 𝐢𝐻4 + 0.160688 𝐢𝑂2 + 0.000552 𝐻2 3 Isobutyric Acid 𝐢4𝐻8𝑂2 + 0.8038 𝐻2𝑂 + 0.0006 𝐻2 + 0.0653 𝑁𝐻3 +0.5543 𝐢𝑂2 β†’ 0.0653 𝐢5𝐻7𝑁𝑂2 + 1.8909 𝐢2𝐻4𝑂2 + 0.446 𝐢𝐻4 4 Isovaleric Acid 𝐢5𝐻10𝑂2 + 0.8044 𝐻2𝑂 + 0.0653 𝑁𝐻3 + 0.5543 𝐢𝑂2 β†’ 0.0653 𝐢5𝐻7𝑁𝑂2 + 0.8912 𝐢2𝐻4𝑂2 + 𝐢3𝐻6𝑂2 +0.4454 𝐢𝐻4 + 0.0006 𝐻2 Methanogenesis 1 Acetic Acid 𝐢2𝐻4𝑂2 + 0.022 𝑁𝐻3 β†’ 0.022 𝐢5𝐻7𝑁𝑂2 + 0.945 𝐢𝐻4 + 0.066 𝐻2𝑂 + 0.945 𝐢𝑂2 2 Hydrogen 14.4976 H2 + 0.0836 𝑁𝐻3 + 3.8334 𝐢𝑂2 β†’ 0.0836 𝐢5𝐻7𝑁𝑂2 + 3.4154 𝐢𝐻4 + 7.4996 𝐻2𝑂 2.1.4 Model description Figure 2 and 3 show the process flow diagram modelled on Aspen Plus of the whole anaerobic digestion and upgrading stages respectively. Figure 2: Microalgae AD Plant Simulation Figure 3: Biogas Upgrading Processing Plant Simulation Hydrolysis is one of the rate limiting steps in AD, and hence the enzymatic pre-treatment improved its efficiency which was modelled in a batch reactor at atmospheric pressure in the presence of Alcalase (Novozymes, 2015) of quantity 0.2 mL/g algaeDM and a density of 1.08 g/mL that degraded the cell walls’ proteins into amino acids. The next step is the anaerobic digestion itself where all reactions of the four phases (hydrolysis, acidogenesis, acetogenesis, and methanogenesis) take place on a kinetic basis (power law) (Table 2). A series of calculator blocks were implemented to compute the rate reactions in the AD in every iteration loop, which are basically written by Fortran code. In total, for glycerol, valeric acid, butyric acid, propionic acid, amino acids, dextrose, oleic acid, methanogenesis, and hydrogen-utilizing processes, eight distinct calculator blocks were utilized. For example, amino acids are transformed into a number of volatile fatty acids (VFA) components after passing through an amino acid calculator block. In order to compute the amount of produced biogas and, consequently, the rate of the reactions, these components pass through multiple VFA calculator blocks, including the valeric acid block and the propionic acid block, followed by the methanogenesis block. 622 For this step, a CSTR was used to operate in mesophilic conditions (35 Β°C),1 atm, and an HRT of 18 days. At this point, the AD is completed with two streams existing the reactor. One is the biogas which will be sent to the upgrading process and the other is the digestate which is centrifuged to separate the liquid part from the solid residues that can be used later as a fertilizer. Once the biogas is obtained, the first stage in the upgrading is drying the biogas, in which it is cooled to 3 Β°C, and hence, water is drained based on its condensation. The dried biogas must now be desulphurized in which the iron oxide adsorption method is adopted. As a result, an absorber of capacity 150 mg/g adsorbent working under 1 atm and at 30 Β°C, is used to ensure that the level of hydrogen sulphide in the final product is below 5 ppm so that it can be directly injected into the natural gas grid (Wasajja et al., 2020). There is still the CO2 to be removed which is done by the amine washing in which the biogas is compressed to 5 bar and sent to an adsorber of 10 stages is used with aqueous MDEA (45 wt%). At this step, the desired product is obtained which is the biomethane at the top of the column while from the bottom the CO2 rich MDEA is regenerated using a stripper of 20 stages. 3. Results and Discussion The main difficulty when building the Aspen Plus AD simulation model is that it needs an analysis of the feed to function properly. Microorganisms are responsible for the anaerobic digesting process but Aspen cannot model their activity. Instead, only the kinetics and reactions that take place during the process are simulated. 3.1 Model Validation Any proposed simulation model must be validated before it can be widely used and hence replicated under different parameters. This can be achieved by comparing the results produced by experimental setups operating in similar environments with the outcomes anticipated by the model. To verify the model's accuracy, the results from the model were compared with experimental data obtained from partners in Almeria, Spain. This experiment used a 55.5 ml/day of feedstock to be processed in a 1.5 L CSTR reactor with a hydraulic retention time of 18 days at an OLR of 1.5 gCOD/(L.day) which were the conditions of the simulation. The experimental results from this study obtained a CH4 concentration of 71.25 mol%. Similarly, the Aspen model simulation obtained a CH4 concentration of 73.4 %. This represents a percentage difference of 2.15 % which allows to conclude that the Aspen Plus model is applicable as the difference between the experimental data from Spain and the Aspen Plus simulation model was minimal. 3.2 Model Upscale and Results After the model is validated, the purpose behind the simulation is to be able to upscale the production from 55.5 ml/day of feedstock to 67 m3/day under the same conditions. In this matter, the model was modified and the following results in Table 3 and Table 4 were obtained. Table 3: Results of the simulation Feed Solid Digestate Biogas Biomethane Mass flowrate (kg/h) 2769.68 1103.75 102.91 50.17 Temperature (℃) 20 35 35 30 Pressure (bar) 1 1 1 5 Table 4: Composition of the obtained biogas and biomethane Component (mol%) Biogas Biomethane CH4 73.4 94.09 CO2 18.4 2.59 H2O 5.52 0.7 H2 1.68 2.6 H2S 214.4 ppm < 1 ppm The results are promising in that a biomethane of 94 mol% purity, reduced CO2 of 2.59 mol%, and low H2S and H2O concentration is obtained and meets the specifications to be able to be introduced directly into the natural gas grid for France and Spain. These specifications include a minimum methane content of 90 mol%, CO2 content less than 3 mol%, and H2 content below 5 mol%, among other criteria (Marcogaz, 2024). Hence, the biomethane obtained can be served as an alternative to natural gas. It has a calorific value of 36 MJ/m3 and hence it was calculated to have an energy output of 73,092.28 MWh. 623 4. Conclusions Microalgae show considerable promise as a supplementary energy supply due to their rapid growth, ease of production, and lack of need for fertile agricultural land. Biogas has been promoted as the simplest energy type to produce utilizing microalgae; thus, substantial attempts are being made to demonstrate its efficiency. This paper highlights the culture and anaerobic digestion of microalgae and determine what information was necessary to model a precise replica using the process modelling software ASPEN Plus. The simulation model covered current research on using microalgae for anaerobic digestion to produce energy. The model included the enzymatic pretreatment to favor hydrolysis. Additionally, it incorporated the anaerobic digestion process as well as the purification of the raw biogas by dehydration, desulphurization, and amine washing to obtain the biomethane. The data gathered from the partners in Almeria, Spain, validated the model, making it suitable for usage as an upscale model up to the desired amount. The simulation results demonstrated an OLR of 1.5 g/L.day and an HRT of 18 days, which achieved a biomethane of 94.1 % purity. Although microalgae have the potential to produce sustainable amounts of biogas, their conversion efficiency and biogas yield are inferior to those of traditional feedstocks, particularly food wastes. Therefore, co-digestion, integrated biorefinery, and strain-improvement technologies should be given priority in enhancing the conversion of microalgae into biogas. Full research is needed, with a special emphasis on cutting-edge reactor designs that guarantee low HRT and high OLR. The generation of sustainable biofuels using microalgae as a feedstock will expand their applicability in the near future under this biorefinery system. As despite the comprehensive modeling and simulation efforts, the optimization of the enzymatic pre-treatment process requires further investigation to maximize biogas yield and cost-effectiveness. The study also requires a thorough economic feasibility analysis for large-scale implementation, which is crucial for commercial viability Lastly, the variability in microalgae feedstock composition and availability, which can significantly affect the anaerobic digestion process, has to be precisely addressed. Future research should focus on these areas to enhance the robustness and practicality of microalgae-based biogas production. Funding Acknowledgments This work has been supported by the European Union’s Horizon 2020 Research and Innovation Program under the topic β€œDeveloping the next generation of renewable energy technologies” [grant agreement #101007006]. Nomenclature CSTR – continuously stirred tank reactor HRT – hydraulic retention time OLR – organic loading rate C/N – carbon to nitrogen ratio References Ayala-Parra P., Liu Y., Field J.A., Sierra-Alvarez R., 2017, Nutrient recovery and biogas generation from the anaerobic digestion of waste biomass from algal biofuel production. Renew Energy, 108, 410–6. Cavinato C., Ugurlu A., de Godos I., Kendir E., GonzΓ‘lez-FernΓ‘ndez C., 2017, Biogas production from microalgae. Elsevier EBooks, 155–182. Gerardo M.L., Van Den Hende S., Vervaeren H., Coward T., Skill, S.C., 2015, Harvesting of microalgae within a biorefinery approach: a review of the developments and case studies from pilot-plants, Algal Res. 11, 248262. Harun R., Singh M., Forde G.M., Danquah M.K., 2018, Bioprocess engineering of microalgae to produce a variety of consumer products. Renew Sustain Energy, 14, 1037–47. IEA, 2020, Outlook for biogas and biomethane: Prospects for organic growth. www.iea.org/reports/outlook-for- biogas-and-biomethane-prospects-for-organic-growth, License: CC BY 4.0. IEA, 2024, Bioenergy. IEA, , accessed 12.10.2024. Marcogaz, 2024, Quality of biomethane required in European countries for injecting into natural gas grid. , accessed 12.10.2024. Novozymes Report, 2015, , accessed 12.10.2024. Rajendran K., Kankanala H.R., Lundin M., Taherzadeh M.J., 2014, A novel process simulation model (PSM) for anaerobic digestion using Aspen Plus. Bioresource Technology, 168, 7–13. Wasajja H., Lindeboom R.E.F., Van Lier J.B., Aravind P.V., 2020, Techno-economic review of biogas cleaning technologies for small scale off-grid solid oxide fuel cell applications. Fuel Processing Technology, 197, 106215. 624