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

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Abstract 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. Summary 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.