Data and code supporting “Quantifying calibration drift in low-cost PM₁₀ sensors across contrasting indoor environments”
Description
This dataset contains measurements from a custom low-cost sensor network deployed in two contrasting indoor environments to evaluate calibration drift in particulate matter (PM₁₀) sensors. Deployments include (1) an industrial painting environment and (2) a swine barn environment. The dataset includes measurements from three co-located low-cost monitors together with co-located reference instruments collected during scheduled reference sampling periods. Variables include PM₁, PM₂.₅, and PM₁₀ concentrations from the low-cost monitors, A-weighted sound levels, temperature, relative humidity, timestamps, and corresponding reference measurements where available. Raw data are provided in CSV and RData formats, together with the R scripts used for all analyses presented in the manuscript. These data support quantification of calibration drift using linear mixed-effects models, comparison of calibration stability across contrasting deployment environments, and evaluation of drift-aware calibration models.
Files
Institutions
- University of IowaIA, Iowa City