A Scalable Calibration Method for Enhanced Accuracy in Dense Air Quality Monitoring Networks.

ABSTRACT: Deployment of large numbers of low capital cost sensors to increase the spatial density of air quality measurements enables applications that build on mapping air at neighborhood scales. Effective deployment requires not only low capital costs for observations but also a simultaneous reduction in labor costs. The Berkeley Environmental Air Quality and CO₂ Network (BEACO₂N) is a sensor network measuring O₃, CO, NO, and NO₂, particulate matter (PM_2.5), and CO₂ at dozens of locations in cities where it is deployed. Here, we describe a low labor cost in situ field calibration for the BEACO₂N O₃, CO, NO, and NO₂ sensors. This method identifies and leverages uniform periods in concentrations across

SUBMITTER: Winter AR 

PROVIDER: S-EPMC11823452 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature