| Project Detail |
There exists a direct relation between gas emissions and earth’s dynamics and climate: the impact of anthropogenic emissions and volcanic eruptions on the climate are well known and from the opposite, the effect of the climate on the volcano activity remains mainly unexplored. To develop climate-volcano models and improve eruption predictive models, a comprehensive study of volcanic emissions is necessary. Reference measuring systems, which are used by the National civil protection agencies and which one can find in the market, are highly sensitive, complex, bulky, expensive and have a high power-consumption. Consequently, they can only be installed in few specific locations. For an accurate spatial monitor of these complex gas mixture emissions, however, a large number of sensing systems need to be deployed and connected, providing the required ubiquity, something which is possible nowadays thanks to Internet of Things (IoT). Usually, these systems do not need to meet the sensitivity level of the reference instruments.
The present project addresses the development, fabrication, and testing of gas sensors for their implementation in IoT systems that will be deployed in the close vicinity of volcanoes. These devices will be made from advanced and harsh-resistant metal oxide (MOX) nanomaterials and will be based on an unexplored dynamic mode (DM) of operation. In opposition to the so-far reported DM systems, based on temperature pulsing, here we propose to use light cycled operation (LCO), in which a single low-power pulsed light-emitting diode photoactivates the MOX, which provides the different gas response patterns required for the correct gas discrimination. This constitutes an electronic-nose and dramatically reduces the number of sensors and power consumption required for gas discrimination. The developed devices will be tested towards gases typically emitted by volcanoes and will be benchmarked against reference measuring systems. |
