Review highlights advances in participatory air pollution monitoring across global communities, suggesting low-cost sensors and improved calibration enhance environmental health research.
Key Points
To critically evaluate the methodological approaches, data reliability, and integration of citizen science air-pollution monitoring into environmental health research and public policy.
Synthesized recent global literature on community-led air monitoring networks, participatory data collection, and low-cost sensor technologies.
Assessed technical integration pathways, including artificial intelligence calibration algorithms, wearable devices, and distributed sensor architectures.
Citizen science networks provide real-time, hyperlocal exposure assessments that improve environmental justice efforts, risk communication, and health-impact modeling.
Advances in wearable monitors and artificial intelligence-driven calibration effectively mitigate longstanding challenges in data accuracy, representativeness, and policy integration.