Citizen Science in Air Pollution Monitoring: Methodological Approaches, Effectiveness, and Integration with Health Research

PURPOSE OF REVIEW: This review critically examines the role of citizen science in air-pollution monitoring and its integration into environmental health research. It explores how participatory approaches, including low-cost sensors and community co-creation, can enhance spatial resolution, public engagement, and environmental justice, while assessing data quality, health relevance, and scalability. RECENT FINDINGS: Recent studies document the expanding global deployment of citizen science air quality monitoring networks. Advances in calibration algorithms, wearable technologies, and participatory data-collection methods have strengthened capacity to assess real-time exposure. Several projects demonstrate the increasing technical sophistication and policy relevance of citizen-generated air quality data. Citizen science provides hyperlocal insights into air quality and exposure, strengthens risk communication, and contributes to health-impact assessment. Although challenges remain regarding data reliability, representativeness, and policy uptake, emerging approaches, including AI-assisted calibration and distributed sensor networks, offer promising pathways forward. An integrative framework can support sustained community engagement and evidence-informed action to improve air quality.