During the second reporting period, WP1 focused on evaluating Co₃O₄ catalyst performance under various feed conditions, including different methane concentrations (10-10000 ppm) and the presence of CO2 and H2O. Water was found to inhibit activity, while CO2 showed minimal effect. Kinetic analysis indicated an activation energy of 71.23 kJ mol⁻¹ and a reaction order of 0.97. Testing for N2O decomposition was initiated. In the case of photo-catalysts, TiO2-based photocatalysts demonstrated effective VOC removal but were inactive for methane oxidation and are being developed as a pre-treatment stage to enhance thermal catalyst stability. Lithium-based zeolite adsorbents, particularly Li₁₃X₃ and Li-SAPO34-5, exhibited high methane adsorption capacities of 1.54 ± 0.12 mmol g⁻¹ and 1.76 ± 0.07 mmol g⁻¹, respectively, maintaining good performance even in the presence of CO2, thus confirming their suitability for methane capture under realistic agricultural conditions.
Work Package 2 has focused on translating the knowledge gathered in the first reporting period regarding sorbent and methods to simulate CH4 adsorption from diluted sources into an optimal process. This process can be used to evaluate the technical challenges and devise solutions for the separation at hand. More specifically: the isotherm modelling work has focused on improving the representation of multi-component mixtures; the process modelling work identified of an optimal process configuration for different objective functions (recovery-purity and energy-productivity), , including design and operation characteristics; sensitivity analyses of the process and material parameters have identified the most important characteristics (mass transfer) and the knowledge gap for further work; the improved simulation technique (acceleration) sped up computation and made optimization easier and faster. Additionally, following discussions on the barn case studies, a possible integration between separation and conversion was investigated, thereby unveiling advantages and disadvantages of the integration, and enabling WP3 to undertake a comparative techno-economic assessment.
WP3 advanced significantly during the last review period, developing a coherent framework to assess the techno-economic performance and the global potential of GHG removal technologies. Task 3.1 defined the structure and scope of a harmonised TEA framework covering bio-CCS, DAC for CO2 and non-CO2 gases, and ocean-based removal, establishing collaboration between several project partners. Efforts were also targeted on understanding when does methane mitigation/removal can be defined as mitigation or removal measure. Task 3.2 performed a first cost assessment of methane and CO2 co-capture from dairy farms, combining process modelling with preliminary techno-economic evaluation. The analysis revealed that methane mitigation from dairy farms is only viable if the co-captured CO2 is permanently stored, yet the total GHG avoidance cost remains very high (> 1350 €/tCO2 eq), primarily due to energy-intensive upgrading and conversion steps. Task 3.3 initiated the integration of non-CO2 removal options into the WITCH model framework, representing methane removal and wetland restoration processes while improving the climate feedback representation.
In WP4, during this period, new farm visits were conducted in Spain, providing updated data on barn design as well as understanding of the real conditions in farms that can suit the implementation of the technology in the future. Also, the Life Cycle Assessment was updated with real farm data, showing refined emission values and including an evaluation of the methane capture technology’s mitigation potential. Energy use for methane mitigation/removal remains the main component in the analysis, and therefore, a lower emission intensity linked with the energy use in the process will enable better life cycle performance. Finally, the validation of the plausibility has advanced with a preliminary study on market trends and social acceptance, integrating insights into consumer behaviour and positioning REPAIR technologies as promising future solutions.
