Building Bridges Through Infrastructure: Citizen Science and Institutional Integration in Air Quality Monitoring
Year: 2026
Type: article
Abstract: Citizen scientists are increasingly using low-cost sensors to measure their surroundings, for example, air quality. Sensor measurements offer greater temporal and spatial resolution, and have the potential to complement official monitoring practices that are often limited in coverage and may not reflect lived experiences. However, integration of citizen science (CS) data into official frameworks is still limited. CS data are often perceived as “messy,” with concerns about data quality, absence of standard methodologies, and perceptions of unreliability. While these challenges are well-documented, the critical role of infrastructure in bridging CS data and institutional frameworks has received less attention. Herein, we examine Measure Together, a government-funded project and community that functions as a boundary organisation at the interface between CS initiatives and institutional air quality monitoring. We explore how infrastructure emerges through relational, organisational, and technical factors aimed at making sense of CS data. We show how this CS infrastructure is beginning to merge with official monitoring infrastructure, resulting in a hybrid infrastructure that seeks to combine local data and insights from CS with the standardised and rigorous approaches of official monitoring. Our analysis highlights critical tensions, including conflicts between local and generic data, the action-oriented expectations of many CS participants versus the long-term timelines of official infrastructure, and challenges around trust and standardisation. We conclude by identifying pathways to navigate these tensions, emphasizing infrastructural work as an integral part of boundary work and a crucial condition for integrating CS and official monitoring data.
DOI: 10.5334/cstp.961
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $613
OpenAlex ID: W7220715883
