Biogas is becoming one of the most used and profitable renewable sources. It is obtained through many different processes that frequently involve different green renewable sources. During the different steps of the process, it generates several by-products that could be reused as organic fertilizers. The aim of this work was to study the volatile fraction and determine the volatile fingerprint of 6 different organic samples involved in biogas production by the innovative Small Sensor System (S3) based on Semiconductor Metal Oxide (MOX) gas sensors. Obtained results show the volatile profile of each sample that at the same time support the sensor's device results. S3 result shows a perfect discrimination of the volatile fraction of the different studied matrices based on the different composition of their volatile set. matrix and shows how the sensors are able, in real time, to cluster and discriminate the fingerprint of these renewable sources. In the end, S3 results are very promising to enhance the traceability and the origin of the sources in the biogas industry at each specific stage of production, focusing on the possible release of off-flavors in the environment from different types of organic biomass and the reuse of their by-products supporting circular economy.
The aim of this work was to find and identify the VOCs set that characterizes different types of organic renewable sources through the use of the tailor made Small Sensor Systems S3 to distinguish between different odor sources based on their qualitative and quantitative differences in VOCs profile, in order to be able in the future to produce a user friendly fast, economic and with auto learning capabilities to support the aforementioned green industrial processes.