Indoor air quality monitoring and source apportionment using low-cost sensors

Abstract

Understanding of the various sources of indoor air pollution requires indoor air quality (IAQ) data that is usually lacking. Such data can be obtained using unobtrusive, low-cost sensors (LCS). The aim of this review is to examine the recent literature published on LCS for IAQ measurements and to determine whether these studies employed any methods to identify or quantify sources of indoor air pollution. Studies were reviewed in terms of whether any methods of source apportionment were employed, as well as the microenvironment type, geographical location, and several metrics relating to the contribution of outdoor pollutant ingress versus potential indoor pollutant sources. We found that out of 60 relevant studies, just four employed methods for source apportionment, all of which utilised receptor models. Most studies were undertaken in residential or educational environments. There is a lack of data on IAQ in other types of microenvironments and in locations outside of Europe and North America. There are inherent limitations with LCS in terms of producing data which can be utilised in source apportionment models. This applies to external pollution data, however IAQ can be even more challenging to measure due to its characteristics. The indoor environment is heterogeneous, with significant variability within the space as well as between different microenvironments and locations. Sensor placement, occupancy, and activity reports, as well as measurements in different microenvironments and locations, can contribute to understanding this variability. Outdoor pollutants can ingress into the space via the building envelope, however measurement of external pollution and environmental conditions, as well as recording details on the building fabric and ventilation conditions, can help apportion external contributions. Whether or not source apportionment models are employed on indoor data from LCS, there are parameters which, if carefully considered during measurement campaigns, can aid in source identification of pollutants.