Table 1:

Proposed Processing Levels for Low-Cost Sensor Systems for Air Quality ^a

Level	Name	Definition	Example: Gas sensors	Example: Particle sensors
Level-0	Raw measurements	Original measurand produced by the sensor system	Voltage corresponding to measured quantity, e.g. current for electrochemical sensors, resistance or conductance for metal oxide sensors or transmitted light intensity for infra-red sensors	Voltage corresponding to light scattered by nephelometers, or to particle counts for bins of optical particle counters
Level-1	Intermediate geophysical quantities	Estimate derived from corresponding Level-0 data, using basic physical principles or simple calibration equations, and no compensation schemes.	For electrochemical sensors, NO2 concentration in μg/m3 or ppb, using only Level-0 data from the NO2 sensor itself with no additional corrections beyond factory calibration. Essentially “raw data in concentration units”.	Binned particle counts or PM mass in μg/m3 derived from Level-0 data using simple calibration and assumed particle density
Level-2A	Standard geophysical quantities	Estimate using sensor plus other on-board sensors demonstrated as appropriate to use for artifact correction and directly related to measurement principle.	NO2 concentration in μg/m3 or ppb, derived from onboard NO2/NO/O3 sensors, corrected for interferences and/or T/RH effects using onboard data	PM concentration in μg/m3, corrected for T/RH effects with onboard-measured T/RH
Level-2B	Standard geophysical quantities-extended	As Level-2A but also using external data demonstrated as appropriate to use for artifact correction and directly related to measurement principle	As Level-2A but using external T/RH from nearby station	As Level-2A but using external T/RH from nearby station
Measurement/prediction boundary
Level-3	Advanced geophysical quantities	Estimate using sensor plus internal/external data to adjust values, not constrained to data inputs proven as causes of measurement bias or related to measurement principle	NO2 concentration in μg/m3 or ppb, corrected for T/RH effects, and using data from nearby meteorological stations or models	PM concentration in μg/m3, corrected for T/RH effects and using data from nearby stations or models
Level-4	Spatially continuous geophysical quantities	Spatially continuous maps derived from network of distributed sensor systems	Map of NO2 concentrations in μg/m3 or ppb, e.g. derived using assimilation of sensor network data into physical model	Map of PM2.5 concentrations in μg/m3, e.g. derived using assimilation of sensor network data into physical model

^aT/RH stands for temperature and relative humidity. The spatial support of all Levels except Level-4 is point measurements at single locations or for entire networks.

^bSee Hagler et al. (2018).(2)