Visualizing Heterogenous Microenvironments

Application of Planar Optodes to Investigate Soil Dynamics - O2, pH and NH3.

Soils are highly diverse and complex ecosystems, with biogeochemical processes occurring at various spatial and temporal scales. Traditional 1-dimensional sensors struggle to quantify the inherent heterogeneity of key soil parameters such as oxygen and pH. However, planar optodes are optical sensors that provide real-time, microscale 2D visualization of chemical analytes in environmental and biological samples. These optodes are valuable for studying the drivers of biogeochemical processes in soils that lead to greenhouse gas emissions like N2O. Despite their potential, planar optodes are mostly limited to laboratory experiments due to practical constraints hindering field measurements.

This Ph.D. study aims to develop a novel, low-cost imaging tool for planar optodes, suitable for in-situ or mesocosm settings. The tool downsizes traditional imaging equipment to fit inside a Ø250mm cylinder, deployable in soils and capable of semi-autonomous, long-term measurements. As proof-of-concept, planar optodes for oxygen successfully captured “panoramic” images with high spatial (≈10 µm) and temporal (minutes to days) resolution in a mesocosm soil setup. Current tests focus on long-term in-situ deployment, measuring daily microscale soil oxygen dynamics down to a depth of 50cm. This is particularly valuable in agricultural settings, where microscale soil dynamics influencing N2O emissions are affected by changing environmental conditions.

The new imaging tool aims to enhance the accessibility of in-situ planar optode applications by providing a standalone hardware and software solution. Future work will include ammonia and pH optodes to visualize microscale variations in these parameters with different fertilizer application techniques. Additionally, the development of new multiparameter optodes and in-situ methods could pave the way for studying complex microscale soil interactions and linking them to large-scale models of greenhouse gas emissions.