Investigating the activity of indigenous microbial communities from Italian depleted gas reservoirs and their possible impact on underground hydrogen storage.

H2 produced from renewable energies will play a central role in both greenhouse gas reduction and decarbonization by 2050. Nonetheless, to improve H2 diffusion and utilization as a fuel, large storage capacity systems are needed. Underground storage of natural gas in depleted reservoirs, aquifers and salt caverns is a well-established technology. However, new challenges arise when it comes to storing hydrogen due to the occurrence and activity of indigenous microbial populations in deep geological formations. In a previous study, four Italian natural gas reservoirs were characterized both from a hydro-chemical and microbiological point of view, and predictive functional analyses were carried out with the perspective of underground hydrogen storage (UHS). In the present work, formation waters from the same reservoirs were used as inoculant during batch cultivation tests to characterize microbial activity and its effects on different gas mixtures. Results evidence a predominant acidogenic/acetogenic activity, whilst methanogenic and sulfate reducing activity were only marginal for all tested inoculants. Furthermore, the microbial activation of tested samples is strongly influenced by nutrient availability. Obtained results were fitted and screened in a computational model which would allow deep insights in the study of microbial activity in the context of UHS.

Design, Fabrication, and Experimental Validation of Microfluidic Devices for the Investigation of Pore-Scale Phenomena in Underground Gas Storage Systems.

The understanding of multiphase flow phenomena occurring in porous media at the pore scale is fundamental in a significant number of fields, from life science to geo and environmental engineering. However, because of the optical opacity and the geometrical complexity of natural porous media, detailed visual characterization is not possible or is limited and requires powerful and expensive imaging techniques. As a consequence, the understanding of micro-scale behavior is based on the interpretation of macro-scale parameters and indirect measurements. Microfluidic devices are transparent and synthetic tools that reproduce the porous network on a 2D plane, enabling the direct visualization of the fluid dynamics. Moreover, microfluidic patterns (also called micromodels) can be specifically designed according to research interests by tuning their geometrical features and surface properties. In this work we design, fabricate and test two different micromodels for the visualization and analysis of the gas-brine fluid flow, occurring during gas injection and withdrawal in underground storage systems. In particular, we compare two different designs: a regular grid and a real rock-like pattern reconstructed from a thin section of a sample of Hostun rock. We characterize the two media in terms of porosity, tortuosity and pore size distribution using the A* algorithm and CFD simulation. We fabricate PDMS-glass devices via soft lithography, and we perform preliminary air-water displacement tests at different capillary numbers to observe the impact of the design on the fluid dynamics. This preliminary work serves as a validation of design and fabrication procedures and opens the way to further investigations.

Computational Analysis of Dynamic Light Exposure of Unicellular Algal Cells in a Flat-Panel Photobioreactor to Support Light-Induced CO2 Bioprocess Development.

Cyanobacterial cell factories trace a vibrant pathway to climate change neutrality and sustainable development owing to their ability to turn carbon dioxide-rich waste into a broad portfolio of renewable compounds, which are deemed valuable in green chemistry cross-sectorial applications. Cell factory design requires to define the optimal operational and cultivation conditions. The paramount parameter in biomass cultivation in photobioreactors is the light intensity since it impacts cellular physiology and productivity. Our modeling framework provides a basis for the predictive control of light-limited, light-saturated, and light-inhibited growth of the Synechocystis sp. PCC 6803 model organism in a flat-panel photobioreactor. The model here presented couples computational fluid dynamics, light transmission, kinetic modeling, and the reconstruction of single cell trajectories in differently irradiated areas of the photobioreactor to relate key physiological parameters to the multi-faceted processes occurring in the cultivation environment. Furthermore, our analysis highlights the need for properly constraining the model with decisive qualitative and quantitative data related to light calibration and light measurements both at the inlet and outlet of the photobioreactor in order to boost the accuracy and extrapolation capabilities of the model.

Analysis of the light intensity dependence of the growth of Synechocystis and of the light distribution in a photobioreactor energized by 635 nm light.

Synechocystis gathered momentum in modelling studies and biotechnological applications owing to multiple factors like fast growth, ability to fix carbon dioxide into valuable products, and the relative ease of genetic manipulation. Synechocystis physiology and metabolism, and consequently, the productivity of Synechocystis-based photobioreactors (PBRs), are heavily light modulated. Here, we set up a turbidostat-controlled lab-scale cultivation system in order to study the influence of varying orange-red light intensities on Synechocystis growth characteristics and photosynthetic activity. Synechocystis growth and photosynthetic activity were found to raise as supplied light intensity increased up to 500 µmol photons m-2 s-1 and to enter the photoinhibition state only at 800 µmol photons m-2 s-1. Interestingly, reverting the light to a non-photo-inhibiting intensity unveiled Synechocystis to be able to promptly recover. Furthermore, our characterization displayed a clear correlation between variations in growth rate and cell size, extending a phenomenon previously observed in other cyanobacteria. Further, we applied a modelling approach to simulate the effects produced by varying the incident light intensity on its local distribution within the PBR vessel. Our model simulations suggested that the photosynthetic activity of Synechocystis could be enhanced by finely regulating the intensity of the light incident on the PBR in order to prevent cells from experiencing light-induced stress and induce their exploitation of areas of different local light intensity formed in the vessel. In the latter case, the heterogeneous distribution of the local light intensity would allow Synechocystis for an optimized usage of light.