Machine learning for high solid anaerobic digestion: Performance prediction and optimization.

Biogas production through anaerobic digestion (AD) is one of the complex non-linear biological processes, wherein understanding its dynamics plays a crucial role towards process control and optimization. In this work, a machine learning based biogas predictive model was developed for high solid systems using algorithms, including SVM, ET, DT, GPR, and KNN and two different datasets (Dataset-1:10, Dataset-2:5 inputs). Support Vector Machine had the highest accuracy (R2) of all the algorithms at 91 % (Dataset-1) and 87 % (Dataset-2), respectively. The statistical analysis showed that there was no significant difference (p = 0.377) across the datasets, wherein with less inputs, accurate results could be predicted. In case of biogas yield, the critical factors which affect the model predictions include loading rate and retention time. The developed high solid machine learning model shows the possibility of integrating Artificial Intelligence to optimize and control AD process, thus contributing to a generic model for enhancing the overall performance of the biogas plant.

Multi-criteria-based decision-making assessment for anaerobic digestion of ammonia-rich distillery wastewater: Effect of pyrochar and temperature.

Energy-efficient wastewater treatment units are imperative to achieve carbon neutrality and a circular economy at the industrial scale. In the present study, pyrochar loading and digestion temperature were tested to assess their impact on the performance of an anaerobic digester running on distillery wastewater. The digestion temperature (37 °C and 55 °C) and pyrochar loading (7.5 - 30 g/L.feed) were selected as two primary design factors. Experiments were designed using Taguchi's design of experiments and specific methane yield, total ammonia nitrogen, pH and buffering capacity were selected as experimental outputs for multi-criteria assessment. The results from the confirmation test indicated that the addition of pyrochar (7.5 g/Lfeed) improved the methane yield (276 ± 15 L/kg VS) significantly compared to the control (167 ± 15 L/kg VS) at 37 °C. The detailed post-digestion analysis showed that the adsorption of ammonia on pyrochar may be the primary reason for enhanced digester performance.

Design, Commissioning, and Performance Assessment of a Lab-Scale Bubble Column Reactor for Photosynthetic Biogas Upgrading with Spirulina platensis.

The two-step bubble column-photobioreactor photosynthetic biogas upgrading system can enable simultaneous production of biomethane and value-added products from microalgae. However, due to the influence of a large number of variables, including downstream processes and the presence of microalgae, no unanimity has been reached regarding the performance of bubble column reactors in photosynthetic biogas upgrading. To investigate this further, the present work documents in detail, the design and commissioning of a lab-scale bubble column reactor capable of treating up to 16.3 L/h of biogas while being scalable. The performance of the bubble column was assessed at a pH of 9.35 with different algal densities of Spirulina platensis at 20 °C in the presence of light (3-5 klux or 40.5-67.5 µmol m-2 s-1). A liquid/gas flow (L/G) ratio of 0.5 allowed consistent CO2 removal of over 98% irrespective of the algal density or its photosynthetic activity. For lower concentrations of algae, the volumetric O2 concentration in the upgraded biomethane varied between 0.05 and 0.52%, thus providing grid quality biomethane. However, for higher algal concentrations, increased oxygen content in the upgraded biomethane due to both enhanced O2 stripping and the photosynthetic activity of the microalgae as well as clogging and foaming posed severe operational challenges.

A perspective on novel cascading algal biomethane biorefinery systems.

Synergistic opportunities to combine biomethane production via anaerobic digestion whilst cultivating microalgae have been previously suggested in literature. While biomethane is a promising and flexible renewable energy vector, microalgae are increasingly gaining importance as an alternate source of food and/or feed, chemicals and energy for advanced biofuels. However, simultaneously achieving, grid quality biomethane, effective microalgal digestate treatment, high microalgae growth rate, and the most sustainable use of the algal biomass is a major challenge. In this regard, the present paper proposes multiple configurations of an innovative Cascading Algal Biomethane-Biorefinery System (CABBS) using a novel two-step bubble column-photobioreactor photosynthetic biogas upgrading technology. To overcome the limitations in choice of microalgae for optimal system operation, a microalgae composition based biorefinery decision tree has also been conceptualised to maximise profitability. Techno-economic, environmental and practical aspects have been discussed to provide a comprehensive perspective of the proposed systems.

How to optimise photosynthetic biogas upgrading: a perspective on system design and microalgae selection.

Photosynthetic biogas upgrading using microalgae provides a promising alternative to commercial upgrading processes as it allows for carbon capture and re-use, improving the sustainability of the process in a circular economy system. A two-step absorption column-photobioreactor system employing alkaline carbonate solution and flat plate photobioreactors is proposed. Together with process optimisation, the choice of microalgae species is vital to ensure continuous performance with optimal efficiency. In this paper, in addition to critically assessing the system design and operation conditions for optimisation, five criteria are selected for choosing optimal microalgae species for biogas upgrading. These include: ability for mixotrophic growth; high pH tolerance; external carbonic anhydrase activity; high CO2 tolerance; and ease of harvesting. Based on such criteria, five common microalgae species were identified as potential candidates. Of these, Spirulina platensis is deemed the most favourable species. An industrial perspective of the technology further reveals the significant challenges for successful commercial application of microalgal upgrading of biogas, including: a significant land footprint; need for decreasing microalgae solution recirculation rate; and selecting preferable microalgae utilisation pathway.