Low-cost sensor data for VOC and BTEX calibration

Description

Uncalibrated and calibrated sensor data used in Frischmon, et. al. "Evaluating machine learning model performance in a two-step colocation process for TVOC and BTEX sensor calibration." The uncalibrated data contains all sensor inputs used to build the calibration models. The calibrated data contains the concentrations predicted from the calibration models. Please note the data was time-averaged (median) to 15-min intervals prior to publication. The first hour of data collection was also removed prior to publication, as the metal oxide sensors require a warm-up period to reach operating temperatures. File name key: {modelname}_colocation_calibrated: The predicted concentrations by a given calibration model during colocation colocation_raw: The raw secondary standard sensor data collected during colocation harmonization_secondary-standard: The raw secondary standard sensor data collected during harmonization harmonization_harmonized: The harmonized sensor data collected during harmonization by field sensors harmonized_raw: The raw sensor data collected during harmonization by field sensors {model_name}_field_harmonized-and-calibrated: The predicted field concentrations by a given calibration model field_raw: The raw sensor data collected in the field Units: VOC concentration- ppb BTEX concentration- ppb NO2 concentration- ppb Uncalibrated sensor data does not have units, as it is an uncalibrated sensor signal.

Institutions

• University of Colorado Boulder

  Colorado, Boulder

Categories

Funders

• National Institute of Environmental Health Sciences

  National Institutes of Health

  Durham

  Grant ID: 1R01ES033478

Licence