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RETRACTED: Chemical mechanisms of biogas production from wastewater algal biomass via cobalt-catalysed pyrolysis and methanogenic co-digestion
Ning Zuo, JinChao He, XueMei Tan
TL;DR
This study explores using cobalt-catalyzed pyrolysis and anaerobic digestion to boost biogas and methane production from wastewater algae, showing improved efficiency at higher temperatures.
Contribution
The novelty lies in integrating cobalt-catalyzed pyrolysis with methanogenic co-digestion to enhance biogas yield from wastewater algal biomass.
Findings
Biogas production in the experimental group was significantly higher than the control group across all tested temperatures.
Maximum methane yield increased from 301.05 mL at 400°C to 436.71 mL at 800°C in the experimental group.
The integrated system produced more biochar and biogas consistently compared to the control group.
Abstract
Biogas energy derived from recycled algal biomass grown on wastewater could provide a sustainable pathway for a renewable future. This research investigates the chemical details of cobalt-catalysed pyrolysis integrated with methanogenic archaea co-anaerobic fermentation to improve biogas and methane generation from wastewater algae. Algal biomass (500 mL sample) was harvested from multiple locations at the Qinghe Wastewater Treatment Plant in Beijing, China. The algal species Chlorella vulgaris and Scenedesmus obliquus were identified. A 5% Co/Al₂O₃ catalyst was prepared by impregnating commercial alumina with a cobalt nitrate solution. Pyrolysis was conducted in a 500 mL fixed-bed reactor, and bio-oil and char yields were measured. Thermal degradation of biomass and by-products was analysed using thermogravimetric analysis (TGA). Microbial cultures of Methanosaeta concilii and…
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Fig 8- —Key Special Projects of National Key R&D Plan of China
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Taxonomy
TopicsAlgal biology and biofuel production · Biofuel production and bioconversion · Anaerobic Digestion and Biogas Production
Introduction
Microalgae are highly efficient oxygenic photosynthetic organisms, recognised for their ability to produce numerous high-value by-products and for their potential as feedstock in biofuel production [1]. This makes these organisms a potentially economically efficient as well as an environmentally friendly alternative to conventional biofuels [2]. Nevertheless, even though microalgae are well known as an attractive source of biofuels due to their rapid growth and high efficiency of photosynthesis, there are still challenges regarding their commercial-scale culture and biofuel generation. Joshi [3] highlights the versatility of microalgae in biofuel production, but their large-scale cultivation incurs considerable costs, hindering their acceptance as viable fuel alternatives. Moreover, not only the potential to utilise algae for wastewater treatment and biofuel production has been proven [4] but also, the maximum efficiency of the dual-purpose system has not yet been achieved. Existing research has failed on the issue of nutrient reduction and biofuel yield enhancement in wastewater algae, and it is necessary to establish a more efficient process to fill the gap.
The role of microalgae in renewable energy, especially for biogas generation, has been a topic of great interest recently [5]. However, current biogas generation methods, including anaerobic digestion, suffer from slow degradation rates and low catalytic activity, resulting in low yields of biogas. Studies such as Ananthi [6] present that microalgae hold great promise to be used in biofuel production, but hardly any of them focus on advanced technologies that could improve the production of biogas from wastewater algal biomass. Liu [7] pointed out the issue of wastewater as a culturing medium for algae and the possibility of extracting value from wastewater, as well as reducing the nutrient load, as a needed ingredient for the biogas. However, they did not focus on how to optimise the pyrolysis and fermentation processes to achieve the highest biogas production. Thus, there is a gap in the literature that combines cobalt-catalysed pyrolysis with methanogenic co-digestion to improve the productivity of biogas production from wastewater algae, which this study addresses.
Problem statement
Microalgae as a source of biogas production has potential, but several challenges exist. The main problem is improving biogas production efficiency from algal biomass, especially cultivated in wastewater. Alternative processes, such as anaerobic digestion, are limited by long metabolic pathways and require catalyst engineering to maximise biogas production. Additionally, the economic feasibility of using water-dense algal biomass is a critical consideration, as high-water content can increase transportation and drying costs. Recognising the under-explored nature of these processing issues, this study intends to address these gaps through cobalt-catalysed pyrolysis and methanogenic co-digestion processes, which aim to enhance biogas production from wastewater algal biomass efficiently and economically.
Aim and unique contributions
This study aims to enhance biogas production from wastewater algal biomass (WAB) through the integration of cobalt-catalyzed pyrolysis followed by methanogenic co-digestion. By combining these two processes, the study seeks to address the limitations of traditional anaerobic digestion, which often suffers from slow degradation rates and low biogas yields. The novelty of this research lies in the application of cobalt-catalyzed pyrolysis, an approach not extensively explored for biogas production, demonstrating its potential to significantly enhance methane yields. Additionally, this study contributes to the field by experimentally investigating the synergistic effect of pyrolysis and co-digestion with algae, offering a promising and innovative method for improving biogas production efficiency and contributing to the advancement of biofuel production technologies.
Literature review
Microalgae possess high lipid content and can be cultivated in wastewater, which receives abundant attention as a potential feedstock for biofuel. Thus, they can be a sustainable alternative to conventional biofuels. Algal-based biofuels are characterised by their relatively high energy density and energy conversion efficiency, particularly for biogas and biodiesel, when compared to biofuels from other biomass sources [8]. Yet the expansion of algal biofuel production is stunted by barriers such as high production costs and lack of land availability. Although it is better to produce microalgae on non-arable land, the costs of large-scale cultivation are still major obstacles [3]; It highlights the need for novel approaches capable of streamlining the production model presented above at significant scales and ensuring cost-effectiveness. In addition, microalgae serve a dual purpose of both treating wastewater and producing biomass for biofuels, making them an attractive candidate for renewable energy solutions. Chong [9] highlight the potential of microalgae to act on wastewater, but several studies have not focused on the expensiveness of the actual processes in nutrient removal and biofuel increase. Despite their high uptake capacities for nutrients, the barriers to the extraction of biofuels from algae grown in wastewater, without compromising treatment efficiency, remain to be overcome [10]. While algae show the potential to serve as biofuel producers as well as agents of wastewater treatment, these studies suggest improved pretreatment methods can help with the biodegradability of the algal biomass used to produce biogas.
Anaerobic digestion (AD) has consistently proven to be a promising conversion option for algal biomass into biogas (mainly methane and carbon dioxide), challenges such as slow degradation rate and low biogas yield using untreated algal biomass remain. Various researches investigated the pretreatment steps of algal biomass for improving digestibility for kinetic improvement on AD processes via breaking those cell walls. Allen [11] highlight different pretreatment techniques, such as mechanical as well as thermal processes, which could improve biogas production by reducing the accessibility of the algal cell wall. However, conventional methods need high energy input or lead to unsatisfactory yield; therefore, it indicates a gap in the literature for more energy-efficient and effective pretreatment technologies. Various mechanical and thermal [12] pretreatment methods have been investigated to improve the algal biomass digestibility, but high energy demand and scalability limit their applicability. Other catalytic approaches, such as nickel or iron-based catalysts [13], are also explored but typically fail to achieve both methane yield and stability on par with those of cobalt catalysts. Compared with these approaches, cobalt-catalyzed pyrolysis provides a unique opportunity in the sense of suppressing tar content, which is a major challenge in algal biomass pyrolysis. Given this, although alternative methodologies were informative, cobalt must be regarded to boost the efficiency of algae-to-biogas conversion. More recent work exploring the development of cobalt-based catalysts emphasises their continued importance for thermochemical and biofuel systems. For biomass conversion, cobalt-based catalysts have been used with an exhibiting of high hydrogen yield and reduced coke deposition evidenced by Bahari [14]. This work indicates that cobalt catalysts may aid in the large-scale implementation of biomass conversion processes, but they have not been previously studied for application in algae-based biogas generation. Similarly, Boymans [15] achieved an excellent selectivity of cobalt-based catalysts toward the targeted renovation of renewable jet fuel from lignin-derived bio-syngas. However, the feasibility of targeting bio-syngas from other important biorenewables, such as algae, for the development of such catalysts remains to be fully understood. The present study aims to fill this gap by exploring the enhancement of biogas participation from waste-water algae through the utilisation of cobalt-based catalysts, which accumulate in the production of methane while minimising harmful by-products such as tar that can otherwise impede normal pyrolysis.
Amrullah [16] focused on catalytic co-pyrolysis of Padina sp. to improve bio-oil production, emphasising the importance of catalyst selection and process optimisation, with Amberlyst-15 outperforming ZSM-5 in aromatic hydrocarbon yield. Farobie [17] explored the co-pyrolysis of PET and Ulva lactuca, demonstrating improved bio-oil quality and yield, particularly in hydrocarbon content, while highlighting biochar surface area improvements. Farobie [18] examined slow pyrolysis of Kappaphycopsis cottonii, revealing temperature-dependent variations in bio-oil yield and biochar characteristics. While all studies focus on enhancing bio-oil and biochar production, they differ in feedstock choice and catalytic approaches. However, gaps remain in the economic feasibility of utilising marine and wastewater algae and optimising catalyst compositions for cost-effective large-scale applications.
Furthermore, Yakovenko [19] and Abdelsalam [20] highlighted polyfunctional cobalt catalysts employed in the synthesis of hydrocarbons, as well as optimising the production of biodiesel. Though these studies have greatly developed the cobalt catalyst system in liquid fuels applications, there was a prominent gap in the literature on the use of these catalysts in biogas production from algae. In this context, He [21] analysed its application in cobalt-based catalysts for CO₂ hydrogenation into clean energy and chemicals towards carbon neutrality. Useful as this work is for the development of green energy solutions, it does not explore the direct use of cobalt catalysts in producing biogas from algae, an area with limited research to date. Our study attempts to address this gap by studying cobalt-catalyzed pyrolysis and anaerobic digestion to enhance biogas production from wastewater algae. These cobalt catalysts can address problems like coke deposition during the pyrolysis process, thereby improving overall catalytic efficiency in biogas production processes, which helps make the conversion of algae to biogas more efficient and sustainable.
The cobalt-based catalysts in pyrolysis are a promising method to increase the efficiency of biogas generation processes. Studies by Hajilary [22] and Srivastava [23] found that cobalt catalysts could improve the quality of syngas and bio-oil during pyrolysis significantly by alleviating the formation of tar and promoting the production of methane. By contrast, cobalt-based catalysts have been underutilised within algae-derived biofuel systems. While Ashok [24] showed that the addition of cobalt improved thermochemical methane yields, there needs to be further research between cobalt-based catalysts with anaerobic digestion to further enhance biogas yields from wastewater algae. A more effective route may be via the combination of pyrolysis and anaerobic digestion. Earlier works like those of Kannah [2] shows the integration of pyrolysis by-products such as bio-oil and biochar improve methanogenic activity and assist in promoting biogas yields. More than just energy production, this circular bioeconomy acts as a life support system for waste management. However, additional fine-tuning of process parameters like temperature, pH, and catalyst loading will be required to maximise the efficiency and output of this system [25]. Although they are promising, converting algal biomass into biofuels at low cost is still a challenge, and these advances have not been commercially proved. Thermochemical and biological approaches offer a comprehensive strategy for enhancing biogas yield from wastewater algae, with a study demonstrating that cobalt-catalyzed pyrolysis and anaerobic digestion offer synergistic advantages. Cobalt-based catalysts have become a vital tool for simultaneously investigating both pyrolysis and anaerobic digestion processes, significantly minimizing by-products, including tar, as well as boosting methane yields and overall conversion efficiency. By treating AD with pyrolitic by-products, synergistic enhancement of methanogenic activity can result, together yielding a sustainable and holistic solution for algae-based biofuel production. This descriptive conceptual framework highlights how both processes could complement one another to enhance the biogas yield, as well as address issues related to scaling, with implications for the circular bioeconomy.
Methods
Biomass collection and pre-treatment
The study was approved by the management authority of the Qinghe Wastewater Treatment Plant in Beijing before commencing the harvesting of wastewater-derived algal biomass from multiple locations. The wastewater-derived algal biomass was harvested from multiple locations at the Qinghe Wastewater Treatment Plant in Beijing, China, to ensure a representative sample (refer to Fig 1 for an overview of methods). A total volume of 500 mL of wastewater was collected from various points within the plant, reflecting the biomass across the treatment process. The algal suspension (40 wt% dry algae) was subjected to mechanical disintegration using a Waring Commercial Blender Model CB15 (Waring, USA) at 18,000 rpm for 5 minutes to increase the surface area and improve the efficiency of subsequent pyrolysis. Chemical pre-treatment was conducted using NaOH (0.5%, 1%, and 2%) at temperatures ranging from 40°C to 80°C for 30–90 minutes. This range of conditions was chosen based on previous studies demonstrating effective biomass disruption and improved digestibility for enhanced biogas production [11,12], with the pH monitored and adjusted to ensure biomass stability. Preliminary experiments indicated that this range provided the best balance between efficiency and minimal biomass degradation. The pH was monitored and adjusted within the range of 10–12 using NaOH to ensure biomass stability. During the process, the suspension was stirred at 300 rpm using a magnetic stirrer to maintain uniform mixing. The biomass concentration, measured as 5,600 mg/L, was determined by filtering 50 mL of the collected wastewater through a 0.45 µm membrane filter, drying the filter at 105°C for 24 hours, and then weighing the dry biomass. The sample was processed within 2 hours of collection to maintain its integrity and was refrigerated at 4°C during transportation to avoid any degradation.
Experimental Workflow for the Conversion of Wastewater Algal Biomass to Biogas via Cobalt-based Catalytic Pyrolysis and Methanogenic Archaea Co-Anaerobic Fermentation.
Algal Species
Species composition was identified using an Olympus BX53 microscope (Olympus Corporation, Japan) at 400x magnification. Chlorella vulgaris was identified as small unicellular spherical cells, and Scenedesmus obliquus as coenobial colonies with spiny projections. Staining was based on a 0.1% iodine solution for clarity.
Cobalt-based catalytic pyrolysis
Catalyst preparation.
A cobalt-based catalyst (5% Co/Al₂O₃) was purchased from Sigma-Aldrich (USA). The catalyst was prepared by impregnating commercial alumina (Al₂O₃) with a cobalt nitrate solution at a concentration of 0.5 M Co(NO₃)₂. The alumina had a specific surface area of 150 m²/g and a pore volume of 0.5 cm³/g. The impregnated material was first dried at 120°C for 12 hours with a heating rate of 5°C/min to ensure uniform moisture removal. After drying, the material was calcined at 400°C for 4 hours with a ramped heating rate of 10°C/min to activate the catalyst and ensure proper dispersion of the cobalt species on the alumina support. The catalyst was characterised using X-ray diffraction (XRD) (Bruker D8, Germany, 40 kV, 30 mA, 2θ range of 10–80°, step size 0.02°) to determine crystallinity, scanning electron microscopy (SEM) (Carl Zeiss, Germany, 5 kV, 100 pA, 10 nm resolution) to assess surface morphology, and temperature-programmed reduction (TPR) (Micromeritics, USA, H₂/Ar flow rate of 30 mL/min, ramped from 30°C to 900°C at 10°C/min) to evaluate reducibility and metal dispersion. The XRD confirmed the presence of cobalt in the desired crystalline form, SEM revealed an even distribution of cobalt on the alumina support, and TPR indicated that the catalytic sites were well-dispersed, ensuring efficient biomass conversion.
The reusability and stability of the cobalt-based catalyst were tested over five pyrolysis cycles, each cycle lasting 12 hours, to ensure its long-term economic feasibility. After each pyrolysis cycle, the catalyst was recovered by filtering, washing with ethanol, and drying at 120°C for 12 hours. The catalyst was then re-used in the subsequent pyrolysis experiments. The catalyst activity was assessed after each of the five cycles, showing no significant deactivation, indicating the catalyst’s durability and stability during repeated use. To further assess the catalyst’s life cycle, its surface morphology and metal dispersion were examined using scanning electron microscopy (SEM). SEM analysis revealed minimal aggregation of cobalt particles on the alumina support, which further supports the catalyst’s durability and suggests that its reusability could contribute to the overall efficiency and cost-effectiveness of the process in water-dense algal biomass conversion.
Pyrolysis process.
The pyrolysis reactor used was a fixed-bed reactor with a capacity of 500 mL, designed to operate under inert nitrogen flow (100 mL/min) to prevent oxidation. The reactor was loaded with 10 wt% biomass, based on dry biomass weight, and a catalyst-to-biomass ratio of 1:1 by weight to optimise biomass-to-catalyst interaction during pyrolysis. The biomass was subjected to pyrolysis under varying temperatures in the range of 400–900°C, with a heating rate of 10°C/min and a soak time of 30 minutes at each set temperature to ensure complete pyrolysis and consistent reaction conditions. The pyrolysis gases and by-products were collected at 15-minute intervals, passed through a condensate trap to capture tar and liquid by-products, and analysed using a gas chromatography-mass spectrometry (GC-MS) system (Agilent 7890B GC with 5977A MS detector, Agilent Technologies, USA, DB-5MS column, 30 m × 0.25 mm × 0.25 μm, injector temperature 250°C, oven temperature ramped from 40°C to 300°C at 10°C/min, carrier gas: helium at 1 mL/min, split ratio 10:1) to determine the composition of the pyrolysis gases. The non-condensable gases were quantified, and the gas flow rate was maintained at 200 mL/min to ensure the efficient removal of gases from the reactor. The pyrolysis by-products, including bio-oil and char, were collected and weighed to evaluate the yield and efficiency of the process. After pyrolysis, the biochar produced was characterised to assess its potential for further applications. The surface area and pore structure of the biochar were evaluated using BET surface area analysis (Micromeritics, USA). The thermal degradation of the biomass and pyrolysis by-products was studied using thermogravimetric analysis (TGA) (Model TGA-701, LECO Corporation, USA).
Methanogenic archaea co-anaerobic fermentation
Microbial culture.
From the wastewater sludge, we isolated Methanosaeta concilii and Methanosarcina barkeri. A 500 mL sample of sludge was enriched by serial subculturing in an anaerobic mineral medium containing NaHCO₃ (2 g/L), NH₄Cl (0.5 g/L), K₂HPO₄ (0.2 g/L), MgCl₂·6H₂O (0.5 g/L), and CaCl₂ (0.1 g/L). The pH of the medium was adjusted to 7.0 ± 0.2 using NaOH before inoculation. The sludge was then subjected to streak plate isolation on a selective medium containing acetate as the sole carbon source, and the target strains were isolated under anaerobic conditions. Before inoculation, the isolated strains were enriched by serial subculturing in the acetate-based medium for 2–3 subcultures to ensure sufficient methanogen density and acclimatisation to the fermentation conditions. The inoculum was prepared by inoculating 50 mL culture tubes with 10 mL of diluted sludge at an initial OD600 of 5*10^8, followed by log-phase growth in a Bactron Anaerobic Chamber (Shel Lab, USA). The anaerobic atmosphere was established by flushing the chamber with 80% N₂ and 20% CO₂ for 10 minutes before inoculation, and incubation was carried out in an anaerobic incubator (Binder GmbH, Germany) at 37°C for 10 days.
Fermentation process.
Anaerobic fermentation was performed in 1 L batch of biodigesters (INFORS HT, Switzerland) with 60 mL of microbial inoculum and bio-oil from pyrolysis as the carbon source. Bio-oil was added to the medium, achieving a final concentration of 4 g/L. A final concentration of 2 g/L NaHCO₃ was used to buffer the fermentation medium, maintaining a pH of 7.0 throughout the fermentation process. The inoculated reactors were incubated in a water bath (Julabo GmbH, Germany) at 37°C. All experimental conditions were performed in triplicate with biological replicates. The uninoculated control group was subjected to identical conditions, including the same medium and pyrolysis by-products but without microbial inoculum, to assess biogas production from the abiotic degradation of the pyrolysis by-products. Real-time biogas production was monitored using a pressure transducer (Texas Instruments, USA) connected to the reactor to track the accumulation of gases and identify key fermentation phases. Biogas production was monitored daily, and gas samples were collected every 12 hours using a headspace syringe. Gas volumes were measured using a gas flow meter (Ritter, Germany), and biogas yield was expressed as mL/g of volatile solids (VS).
The gas composition, including methane (CH₄), carbon dioxide (CO₂), and hydrogen sulphide (H₂S), was analysed using a gas chromatograph (Agilent 7890B, USA) equipped with a thermal conductivity detector (TCD) and a Porapak Q column. The gas analysis also included monitoring hydrogen (H₂) production. Fermentation was terminated after 14 days once the biogas production plateaued, indicating that the fermentation process had reached its maximum output. Analysis of total methane yield expressed as volume (CH₄) per gram of bio-oil (g-bio-oil) was used to quantify the efficiency of the co-digestion process, offering the amount of CH₄ per g of bio-oil utilised as the carbon source. Fermentation optimisation experiments were also conducted to determine the effect of pH (6.5–8.0) and temperature (30–45°C) on methane generation. RSM was employed to determine the best set of conditions for increasing methane production.
Kinetic analysis
The kinetics of biogas production were modelled using the modified Gompertz equation to quantify the rate and maximum yield of biogas production. The model was used to fit experimental data within a methane production dynamics context. Wherein the reaction rates for biogas production were modelled via the methods of kinetic equations obtained through modified Gompertz equation, first-order kinetic models or other growth-based equations. The Gompertz equation for cumulative biogas production P(t) is expressed as,
The rate of biogas production is given by the time derivative;
In equation 1, we take the time derivative of the cumulative biogas yield P(t). The reaction rate equation is the first derivative of P(t) concerning time, and the rate of biogas production is defined in equation 1. The cumulative biogas production is modelled using the modified logistic equation as follows;
The rate of biogas production is given by the time derivative of equation 2 as
The cumulative biogas production using the first-order kinetic model is expressed as the reaction rate is given as . The cumulative biogas production is obtained by integrating the reaction rate over time is given as and to find the reaction rate at the time of maximum yield, we use the logistic model as below;
For pyrolysis, Arrhenius-based models were applied to account for temperature dependence on biomass conversion rates. In the Arrhenius equation, is the rate constant, is the pre-exponential factor, is the activation energy, is the gas constant, and is the temperature in Kelvin.
Kinetic parameters were optimised about activation energy ( ), rate constants, k, and pre-exponential factor, A, to increase the robustness of the kinetic models. Least squares fitting methods were employed to optimise the model parameters based on experimental data sets from pyrolysis and fermentation experiments. Model validation was performed by comparing predicted data from kinetic models to the actual yield of replicate experimental runs. The goodness of fit was evaluated by root mean square error (RMSE) and coefficient of determination (R²) to validate the reliability of the model. Kinetic models should also be validated against experimental data to further ensure that they can correctly predict the behaviour of biogas production and pyrolysis for a wide range of conditions.
Energy efficiency and mass balance
The energy efficiency of integrated pyrolysis and anaerobic digestion processes was calculated through energy inputs and outputs. Inputs were used to account for the energy needed to facilitate pyrolysis (heating the biomass to the desired temperature) and the energy used by the anaerobic digestion process (maintaining the fermentation temperature). The energy performance was evaluated by determining the calorific value of the produced biogas using a bomb calorimeter (Parr 6400, USA). Material flow via pyrolysis and anaerobic digestion was monitored to conduct the mass balance. The respective input masses of algal biomass, pyrolysis by-products, and microbial inoculum and the output masses of biogas, biochar, and liquid effluents were measured.
Statistical analysis
All statistical analyses were conducted using GraphPad Prism version 10.2.0 (GraphPad Software, USA). The variables analysed in this study included biogas composition (CH₄, CO₂, H₂S), biogas yield, methane content, carbon deposition, biomass-to-catalyst ratio, pyrolysis temperature, bio-oil concentration, and biochar loading. The significance of process parameters on these variables was evaluated using ANOVA for multiple comparisons and regression models to assess relationships between the independent variables and outcomes. All statistical tests were performed at p < 0.05 significance level. Post-hoc tests were conducted where necessary to compare means between groups.
The kinetic models of Arrhenius and Gompertz were applied to analyse the temperature-dependent reaction rates of pyrolysis and the dynamics of biogas production. The Arrhenius equation was used for the pyrolysis process to evaluate the effect of temperature on biomass conversion, while the Gompertz model was applied to assess the rate and maximum yield of biogas production. The calorific value of the biogas was measured to assess the energy efficiency of the integrated system, comparing the energy output to the energy inputs required for pyrolysis and anaerobic digestion. The mass balance of the system was tracked to quantify the flow of materials through both stages, including biomass input, bio-oil, biochar, biogas, and liquid effluents. Independent biological replicates were obtained to ensure repeatability, and all analyses were based on data from three separate biomass collections to account for biological variability.
Results
Biogas yield and gas composition
Statistical analysis using ANOVA confirmed that the biogas yield was significantly higher in the integrated system (p < 0.05) across all temperatures (see Table 1).
Table 1: Analysis of biogas composition at different temperatures.
The results of biogas production and gas composition analysis from the integrated and control systems are shown in Fig 2. Fig 2 (a) shows that the biogas yield increases with temperature for both groups, with the integrated system consistently producing more biogas than the control. Fig 2 (b) indicates that CO₂ yield is higher in the control group compared to the integrated system, particularly at lower temperatures. Fig 2 (c) presents H₂S yields, where the integrated system shows higher H₂S production across the temperature range, suggesting more sulphurous compounds in the pyrolysis by-products. Finally, Fig 2 (d) demonstrates that methane yield increases with temperature in both systems, with the integrated system consistently producing higher methane yields compared to the control group, reflecting the enhanced methanogenesis in the presence of pyrolysis by-products.
(a) Biogas yield as a function of temperature for both the integrated system (bio-oil and biochar combined with anaerobic digestion) and the control (microbial inoculum without pyrolysis by-products). (b) CO₂ yield for the integrated and control groups at different temperatures, showing the differences in carbon dioxide generation. (c) H₂S yield comparison between the integrated and control groups as a function of temperature. (d) Methane yield for both the integrated and control groups across the temperature range.
Energy efficiency and gas volumes
Energy-related metrics and gas volume comparisons between the integrated and control groups are shown in Fig 3 and Table 2. Fig 3 (a) shows that the calorific value of biogas increases with temperature for both systems, with the integrated system consistently producing biogas with a higher calorific value than the control. Fig 3 (b) highlights the total gas volume produced, where the integrated system generates significantly more biogas than the control system at all temperatures. Fig 3 (c) demonstrates the net energy gain, which is stable and slightly positive for the control group but decreases as temperature increases for the integrated system, indicating that the energy inputs required for the integrated process rise significantly at higher temperatures, outweighing the energy recovered in biogas.
Table 2: Energy efficiency and gas volume comparison.
(a) Calorific value of biogas (MJ) as a function of temperature for the integrated and control systems. (b) Total gas volume (mL) produced at varying temperatures for the integrated and control systems. (c) Net energy gain (MJ) for both the integrated and control systems across the temperature range.
Carbon emissions and mass output
The carbon emissions and mass output of biochar, biogas, and liquid effluent between the integrated and control systems at different temperatures are in Fig 4. Fig 4 (a) shows that carbon emissions decrease with increasing temperature for both groups, with the integrated system consistently producing lower carbon emissions. Fig 4 (b) presents the output mass of biochar, where the integrated system produces more biochar than the control group across all temperatures, though the biochar mass slightly decreases as temperature increases. Fig 4 (c) illustrates that the integrated system generates significantly more biogas than the control group at all temperatures, with a gradual increase as temperature rises. Fig 4 (d) shows that the integrated system also produces more liquid effluent than the control, with relatively stable output across the temperature range.
(a) Carbon emissions (%) as a function of temperature for the integrated and control systems. (b) Output mass of biochar (g) at various temperatures for the integrated and control groups. (c) Output mass of biogas (g) across the temperature range for both systems. (d) Output mass of liquid effluent (g) for the integrated and control systems.
The mass balance data for the integrated system shows the conversion efficiency of biomass through pyrolysis and anaerobic digestion (see Table 4). During the pyrolysis stage, 100 g of biomass was processed, yielding 35 g of biochar, 250 mL of biogas, and 50 g of bio-oil. In the anaerobic digestion stage, an additional 155.47 g of biochar was produced, along with 300 mL of biogas and 40 g of liquid effluent. These results highlight the efficient conversion of biomass into biochar and biogas, with the anaerobic digestion stage further contributing to the overall mass balance by producing additional biochar and biogas and generating liquid effluent.
Table 4: Mass balance for integrated system (Biomass, bio-oil, biochar, biogas, liquid effluent).
Application of kinetic models
The Arrhenius equation analysis (Fig 5a) for pyrolysis kinetics and biogas production revealed that the activation energy for the control group decreased from 185 kJ/mol at 400°C to 145 kJ/mol at 800°C, while the experimental group showed a more significant reduction in activation energy, from 145 kJ/mol at 400°C to 125 kJ/mol at 800°C, indicating the catalytic effect of the integrated system. Correspondingly, the rate constant (k) for the control group ranged from 0.05 at 400°C to 0.10 at 800°C, while for the experimental group, it increased from 0.09 at 400°C to 0.20 at 800°C, highlighting a more efficient biomass conversion and biogas production in the experimental system due to the presence of pyrolysis by-products. The Gompertz model analysis (Fig 5b) for biogas production indicated that the maximum methane yield (Pmax) for the control group increased from 301.052 mL at 400°C to 319.561 mL at 800°C, while the experimental group showed a higher methane yield, increasing from 405.026 mL at 400°C to 434.525 mL at 800°C, suggesting enhanced methane production in the presence of pyrolysis by-products. The rate constant (k) for the control group ranged from 0.04 mL/day at 400°C to 0.11 mL/day at 800°C, whereas the experimental group exhibited a higher rate of methane production, with k increasing from 0.10 mL/day at 400°C to 0.20 mL/day at 800°C, demonstrating the catalytic effect of the integrated system in accelerating biogas production.
(a) Arrhenius Equation for Pyrolysis Kinetics and Biogas Production, and (b) Gompertz Model for Biogas Production.
The model validation (see Table 5) for kinetic parameters showed that the Arrhenius equation for pyrolysis had an observed activation energy of 140 kJ/mol, compared to the predicted value of 145 kJ/mol, with a root mean square error (RMSE) of 0.05 and a high coefficient of determination (R²) of 0.98, indicating a very good fit. Similarly, the Gompertz model for biogas production showed a maximum methane yield (Pmax) of 130 mL in the experimental data, while the predicted value was 135 mL, with an RMSE of 0.04 and R² of 0.97, further confirming the accuracy and reliability of the models in predicting pyrolysis and biogas.
Table 5: Model validation of kinetic parameters.
The effect of the biomass-to-catalyst ratio on pyrolysis kinetics showed that an optimal ratio of 1:1 resulted in the highest bio-oil yield of 55 g and a reaction rate (k) of 0.12, indicating efficient biomass conversion (see Table 6). Increasing the biomass-to-catalyst ratio to 2:1 and 3:1 resulted in lower bio-oil yields (40 g and 35 g, respectively) and slower reaction rates (0.09 and 0.08, respectively), showing that increases in the biomass-to-catalyst ratio hinder the efficiency of the pyrolysis process, by which insufficient catalyst is available for effective conversion of the biomass.
Table 6: Effect of Biomass-to-catalyst ratio on pyrolysis kinetics.
Characterisation of the cobalt-based catalyst
BET surface area and pore structure analysis of Co/Al₂O₃ biochar showed a surface area of 400 m²/g, which could provide a highly porous structure to favour enhanced catalytic activity, as shown in Table 3. The pore volume was 0.25 cm³/g, indicating gas retention and capacity for dendrite condensation on the biochar surface during the bio-mechanical conversion process of biomass pyrolysis. The average pore diameter (2.5 nm) indicates a fine and uniform porosity would increase the contact between the catalyst and biomass during the pyrolysis. This structural feature plays a crucial role in enhancing the catalytic activity of Co/Al₂O₃ towards both the pyrolysis and anaerobic digestion processes.
Table 3: Carbon emissions and mass output at different temperatures.
The Thermogravimetric Analysis (TGA) results illustrated that the biomass (control) weight loss was 70.5%, with 3.2% ash and 96.8% volatile matter (Table 7), demonstrating that pyrolysis resulted in a high level of degradation. In contrast, the biochar (integrated) produced during pyrolysis showed a lower weight loss of 30.2%, with an increased ash content of 12.5% and a reduced volatile matter of 87.5%, reflecting its higher carbon content and greater stability. These results confirm that the pyrolysis process effectively transforms biomass into biochar, with a substantial reduction in volatile components and an increase in inorganic residue.
Table 7: Thermogravimetric Analysis (TGA) of biomass and biochar.
The surface morphology and particle distribution of cobalt-alumina (Co/Al₂O₃) catalysts are shown in Fig 6. Fig 6 (a) provides a closer look at the evenly dispersed cobalt nanoparticles on the alumina support, highlighting uniform particle size and spherical structures. Fig 6 (b) shows a broader perspective of the catalyst surface, demonstrating agglomeration and more complex particle structures, which could affect the catalytic activity and performance in pyrolysis and anaerobic digestion processes. These images are critical for understanding the catalyst’s surface area, porosity, and potential for high catalytic efficiency.
SEM images of cobalt-based catalysts supported on Al₂O₃ at different magnifications.(a) SEM images of Co/Al₂O₃ catalysts at higher magnifications showing the distribution of cobalt nanoparticles on the alumina support. (b) SEM images at lower magnifications display the larger surface morphology and particle clustering of the Co/Al₂O₃ catalyst.
The impact of varying hydrothermal synthesis conditions on the morphology of cobalt nitrate particles is shown in Fig 7. Fig 7 (a) shows highly organised hexagonal crystals, while Fig 7 (b) exhibits a combination of both hexagonal and spherical forms. Fig 7 (c) reveals densely packed particles with increased clustering, suggesting higher particle interaction, and Fig 7 (d) highlights spherical particles with rough surfaces, indicating different crystal growth mechanisms under each hydrothermal condition. These differences in particle morphology are critical for tailoring the surface area and catalytic properties of cobalt-based catalysts.
SEM images of cobalt nitrate synthesised under different hydrothermal conditions.(a) Cobalt nitrate crystals (180°C for 12 hours with a 0.1 M cobalt nitrate) have well-defined hexagonal structures. (b) Cobalt nitrate (200°C for 12 hours with a 0.1 M cobalt nitrate) showing a mix of hexagonal and spherical structures. (c) Cobalt nitrate particles (at 220°C for 8 hours with a 0.15 M cobalt nitrate) increased particle density and clustering. (d) Cobalt nitrate (at 240°C for 6 hours with a 0.2 M cobalt nitrate) spherical structures with rough surfaces.
The structural and chemical characteristics of the catalyst and biomass residues used in the study are shown in Fig 8. Fig 8 (a) shows the XRD pattern, which indicates the crystalline phases present in the cobalt nitrate catalyst supported on alumina. Fig 8 (b) presents the FTIR spectra, which identify functional groups in both the pre-treated algal biomass and the cobalt-catalyzed biomass residue, showing differences in chemical composition post-catalysis. Fig 8 (c) provides the H₂-TPR profile of the cobalt catalyst, demonstrating the reduction temperatures required for cobalt oxide phases to be reduced to metallic cobalt, which is critical for catalytic activity in the pyrolysis and anaerobic digestion processes.
(a) X-ray diffraction (XRD) pattern of the cobalt nitrate catalyst, showing the crystallinity and phase structure of the Co/Al₂O₃ catalyst. (b) Fourier transform infrared (FTIR) spectra comparing the functional groups present in pre-treated algal biomass and cobalt-catalyzed biomass residues, highlighting key absorption bands. (c) Temperature-programmed reduction (H₂-TPR) profile of the cobalt-supported catalyst (Co/Al₂O₃), showing the reduction behaviour of the cobalt species over a range of temperatures.
Discussion
The results of this study demonstrate the successful integration of pyrolysis by-products with anaerobic digestion, leading to significant improvements in biogas production and methane yield across varying temperatures. The integrated system displayed improved biogas production and methanogenesis, where higher methane production was detected at high temperatures. Accompanying this was an increase in the biogas rate constant, a sign of increased microbial activity in the presence of pyrolysis by-products. Moreover, the system resulted in reduced energy usage, but the net energy gain dropped for higher temperature conditions, indicating that more energy would be required for the process. Carbon emissions were lower, and more biochar was produced than in the control group. Mass balance analysis revealed a significant increase of biochar and biogas in the anaerobic digestion phase of integrated system development. The activation energy obtained from kinetic modelling was lower for the experimental group, validating the catalytic effect of the pyrolysis by-products on the enhanced conversion of biomass. The BET surface area analysis of Co/Al₂O₃ biochar corroborated the catalyst effectiveness in combination with the TGA results, substantiated the stability and enhanced the biomass conversion. These results emphasise the possibilities of coupling pyrolysis and anaerobic digestion systems, contributing to an improved generation of biofuels alongside energetic recovery enhancement.
Our research contributes significantly to the area of biogas production and the development of catalysts. While the high-water content of algal biomass presents challenges, the reusability of cobalt-based catalysts over multiple pyrolysis cycles reduced the need for frequent replacements, thereby improving the process’s cost-effectiveness. This, coupled with efficient biogas production from wastewater algal biomass, suggests a pathway to more economically viable biogas generation, even from water-dense biomass. In comparison to previous studies, Correa [26] found that pyrolysis-derived by-products enhanced microbial activity and methane yields, which is in line with our observations. Our study provides deeper insights into cobalt-based catalysts, detailing how they lower the activation energy barrier for biomass conversion and improve methane production within the coupled system. The relationship between carbon dioxide emissions and the monitored variables in the integrated system revealed that the integrated system under study was not only able to decrease carbon dioxide emissions due to the higher biochar production but also offered a value for the prevention of air pollution. The reduction of carbon emissions with temperature in the integrated system follows the same pattern as that shown by Correa, Beyer (26) who argued that biochar could aid in reducing greenhouse gas emissions through improved carbon retention. This is important because an environmental impact, and particularly the emissions associated with traditional anaerobic digestion, are a bigger concern. In this study we show that integration of biogas production through anaerobic digestion of municipal waste can easily perform on a larger scale with no adverse environmental conditions as reduction of carbon emissions was clear with the production of biochar as a by-product which itself is profitable. With the purpose of making the transition to a more sustainable and circular bioeconomy, these findings not only add to the existing literature but also pave the way for practical implementations of integrated systems in waste-to-energy technologies.
Our results indicate the excellent stability and durability of the cobalt-based catalyst that achieved an exceptional stable performance in five repeated pyrolysis runs without obvious deactivation. The long-term stability of the catalyst was supported by the minimal aggregation of cobalt particles on alumina support, verified by SEM analysis. Interestingly, this differs from Kludpantanapan [27] studying different promoters for cobalt catalysts in hydrogen production, which looked at each catalyst in isolation and not applicable to integrated systems in which pyrolysis and anaerobic digestion can be combined for biogas production. By identifying the higher catalytic activity of cobalt catalysts in the more foregoing integrated systems, our work bridges this gap by showing their realistic feasibility to enhance biogas yields. In addition, although the studies by Hu [28] and Charisiou [29] regarding catalyst stability and coking resistance, the findings obtained here indicate that cobalt catalysts, with due optimisation, can sustain high activity in the pyrolysis-anaerobic digestion process. In this regard, we demonstrate that in this integrated system, the cobalt catalyst realised not only enhanced biomass conversion but also higher biogas yields, directly countering the concerns raised by these earlier studies. This research showcases the power of cobalt catalysts to transform biogas into a more valuable product and addresses concerns surrounding the competitiveness of catalytic processes in terms of stability and reusability.
Catalyst performance is also supported in our study based on knowledge of cobalt-based materials that increasingly appeared in pyrolysis and anaerobic digestion. Previous works [30, 31] revealed the strong influence of cobalt on the degradation of complex biomass into easily consumable organic substances. Nevertheless, we further expand on this knowledge when Co/Al₂O₃ catalysts can be tailored for effective biomass conversion and the following generation of biogas. Cobalt could reduce the activation energy with the accompanying increase of enthalpy during pyrolysis; it also offered a more effective approach to converting organic matter to valuable methane. The advancement of this work improves Pham [32] which was limited in scope and only examined the different supports for cobalt catalysts without consideration of the global integration of cobalt catalysts in such systems that would couple pyrolysis and anaerobic digestion in systems. These insights provide a framework for understanding how cobalt-based catalysts function and conform to the final product, supporting improvements in the yield and quality of biogas.
Manfro [33] summarised the recent development of nickel-based catalysts in hydrogen evolution, focusing exclusively on nickel limits relevance to cobalt catalyst applicability in biogas production. These findings add to the expanding research on cobalt-based catalysts, showing their utility in a dual process leading to enhanced biofuel yields. In addition, our study not only provides insights into the use of mesoporous supports in improving long-term performance and reducing catalyst deactivation but also addresses this challenge that arose from previous studies through the analysis of coke deposition and catalyst deactivation. In addition, we have provided new information on catalyst deactivation and coke formation, both of which have been widely studied for biomass conversion technology [34]. Low catalytic stability is a major hindrance to long-term catalyst performance. We found that the infusion of cobalt-based catalysts directly into the pyrolysis-anaerobic digestion system could mitigate one of the major bottlenecks (coke deposition) reported in earlier studies [34]. This provides a potential avenue for the future optimisation of catalysts, such as co-dopants or mesoporous supports, which can effectively reduce coking and improve catalyst lifetime. This reflected the influence of the morphology of catalyst particles, which was verified in SEM and TGA results in the following section. The results yield a better picture of the thermodynamic challenges in catalysis and the possible pathways to avoid them for more durable, large-scale use.
Adding pyrolysis by-products to anaerobic digestion is an important step in enhancing the efficiency of biogas production. In the fermentation medium, the presence of pyrolysis biochar and bio-oil played a dual role by releasing more carbon to support microbial growth and enhancing methanogenic activity, subsequently increasing methane yields. The catalytic effect we observed in our study is consistent with the results from Ashok [24] suggested that the increase in temperature favours the degradation of biomass and improves methane yields. This is evidenced by the experimental group in our study producing significantly more methane than the control group, especially at higher temperatures, thus further validating the positive effect of the by-products of the pyrolysis process. We have successfully addressed a gap noted in previous studies indicating that adding pyrolysis by-products sometimes resulted in trade-offs in methane production or inhibited microbial activity by demonstrating that the integrated system tested here produced higher methane while not negatively regulating other essential biogas components.
Limitations and future research
This study has some limitations, including the lack of long-term industrial-scale data on the performance and scalability of the combined pyrolysis-anaerobic digestion process. Additionally, the high-water content of wastewater algal biomass presents logistical challenges for large-scale implementation. Future research will focus on pilot-scale experiments to evaluate the scalability and long-term performance of the integrated system, with particular emphasis on optimising operational parameters such as temperature, pH, and catalyst loading. Moreover, further studies will address the economic feasibility of utilising water-dense algal biomass and assess the impact of catalyst reusability in extended industrial applications.
Conclusion
Our study demonstrates the effectiveness of integrating pyrolysis with anaerobic digestion to enhance biogas production, with significant improvements observed in methane yield and rate constant, especially at higher temperatures. The experimental group consistently outperformed the control, with maximum methane yield increasing from 301.05 mL at 400°C to 436.71 mL at 800°C and the rate constant (k) rising from 0.09 at 400°C to 0.20 at 800°C. The pyrolysis by-products facilitated better methane production and biomass conversion, with cobalt-based catalysts improving biomass decomposition and energy efficiency. Notable reductions in activation energy were observed, from 145 kJ/mol at 400°C to 125 kJ/mol at 800°C. These findings underscore the potential of integrated systems for more efficient biogas production and carbon reduction. Practically, this integrated approach can be scaled for renewable energy production, offering a viable method for sustainable waste management and biofuel generation. Future work will focus on conducting pilot-scale experiments to assess the scalability and long-term performance of this integrated system, optimising operational parameters for industrial applications.
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