Opportunities and challenges of sensor technology for indoor air quality monitoring

Indoor air quality (IAQ) plays a vital role in providing healthier indoor environments, especially considering that most human activities occur indoors. Since indoor and outdoor air pollutants are closely interrelated, monitoring both can provide insights into IAQ dynamics.
The IDEAL (Indoor Air Quality Health) Cluster comprises seven Horizon-Europe funded projects (InChildHealth, INQUIRE, LEARN, K-HealthinAIR, SynAir-G, TWINAIR, and EDIAQI) and the Working Group (WG) on Sensors aims to enhance understanding of knowledge gaps in IAQ, identifying IAQ determinants and to assess their health impacts using various sensor technologies. The goal of the WG on Sensors is to develop common documentation on sensor types, operation modes, characterization, calibration, performance, assessment and validation methods for indoor air quality monitoring and health impact assessment.
The documentation is informed by the different technologies and methodologies used across the seven EU-projects. We have found that the most commonly measured parameters include particulate matter, total volatile organic compounds (TVOC), CO2 and comfort parameters (temperature and relative humidity) although other parameters are also monitored based on the specific needs of each project. Low-cost sensors for indoor air quality monitoring are used across all the IDEAL cluster’s projects, although they come from different manufacturers. For example, VOCs are monitored using metal oxide sensors from Sensirion, Alphasense, and Figaro, with non-distinction of the VOC species to be the common challenge across all low-cost sensors. All the projects have planned for co-location to understand the data quality. Sensor-measured particulate matter is mainly validated against reference measurements in the field, and in two out of seven projects co-location campaigns conducted in various European countries to assess how the sensors respond in different indoor environments. In this transfer learning approach, all projects share their experiences, highlighting the advantages, limitations, and challenges associated with using different sensor technologies to measure air pollutants. All information gathered is mapped to identify possible similarities and challenges in measuring common parameters across the seven IDEAL Cluster’s projects. This information can be proven useful also to projects pertaining to other citizen science initiatives that are interested in monitoring IAQ.