Calibration strategies for low-cost compact field sensors in Citizen Science Air Quality measurements: Insights from SOCIO-BEE project

Low cost sensors (LCSs) have the potential to revolutionise environmental monitoring by complementing traditional regulatory agencies’ air quality monitoring, thereby marking a paradigm shift in data acquisition. LCSs can create dense observation networks, providing high spatial and temporal resolutions at affordable cost, leveraging the public participation and engagement, in order to support scientific research and decision-making. Calibration of LCSs is of utmost importance to ensure data quality and their consolidation in scientific research and regulatory activities. Their accuracy, drift (due to time, temperature and/or humidity) and cross-sensitivity to non-target analytes challenge their use in official air quality databases, creating concerns regarding data quality and performance stability. It is common practice to colocate one or more sensors with reference monitoring air quality stations. However, it is of immense significance to outpace the limitations of LCSs under real-world conditions during citizen science (CS) experimental campaigns performed exclusively by citizen scientists, which so far have received little attention by the scientific community and constitute a barrier to effective decision making. This paper discusses the requirements for accurate sensor calibration and validation, by: i) employing various citizen- and expert-operated calibration strategies, ii) including pre-deployment and post-deployment validation and iii) evaluating the impact of the duration of colocation (short-term and long-term) on the acquired results. Thus, in order to shed light to these questions, we employ data from two small networks of LCSs one in Municipality of Ancona, Italy and one in Municipality of Amaroussion, Greece, deployed through the EU-funded project SOCIO-BEE. We present a preliminary feasibility assessment of the feasibility of CS-based calibration measurement campaigns and finally we conclude this study with future scope to improve sensor calibration strategies in CS experiments for air quality measurements to be employed in similar CS projects.