SensMOFAir-2020

Monitoring of indoor and outdoor air pollution has become a key point in our everyday life. In particular, the European Commission calls on Member States to implement air quality action plans, which would ensure compliance with European directive standards. According to Markets and Markets, the global market for gas sensors, detectors and analyzers is expected to grow at an annual rate of 5.7% between 2016 and 2021 to reach $ 4 billion. Over the same period, the global market for electronic test and measurement instrumentation is expected to grow at an annual rate of 4.9%. Air quality management is currently based on a network of a small number of high precision fixed stations with very high purchase, operation and maintenance costs. Hence, there is currently a new paradigm for air pollution monitoring based on the use of ubiquitous network of low-cost sensors for real-time and high spatiotemporal resolution monitoring of air pollutants concentrations. The very few studies about the performance assessment of such low-cost sensors vs their more expensive counterparts show the sensors performance getting deteriorated under real-world conditions because of both ageing and influence of gaseous co-pollutants. In this respect, the aim of SensMOFAir-2020 project is to develop low-cost metal oxide gas sensors (MOS) for real-time and continuous measurement of air pollution, with high detection performance and low energy consumption. All together, these criteria will allow a massive, distributed and ubiquitous monitoring of ambient air quality. To overcome the major obstacle for a widespread use of MOS gas sensors (low selectivity), nanostructured sensitive layers developed and integrated on micromachined platforms will be further functionalized with selective molecular sieve filters improving sensors selectivity. Final products developed in this project (prototypes of selective gas sensors) will be tested in real environment with the involvement of the industrial partner. In the near future, such sensors could integrate omnipresent sensor networks and allow a dramatic increase in the volume of air quality data with high spatial and temporal resolution. Finally, these sensors are expected to i) supplement conventional air quality monitoring, ii) improve the link between pollutant exposure and human health, iii) help for emergency response management and last but not least iv) increase community's awareness and engagement towards air quality issues.