Reference Projects
Carbosense: Switzerland
BEACO2N: California/Berkeley
Ameriflux: https://ameriflux.lbl.gov/
NASA Instep: https://www.nasa.gov/centers/ames/earthscience/programs/instep
Calibration
- Sensors were calibrated in a pressure and climate chamber*
- Sensor unit not equipped with pressure sensor, pressure has to be measured independently or estimated from other information sources*
- BEACO2N calibration and drift compensation: https://amt.copernicus.org/articles/14/5487/2021/ — initial calibration done in the lab, then remotely.
- employed sensor model is based on the Beer-Lambert law and extended by an empirical parametrisation that can relate the sensor IR measurements and the ambient CO2 molar fraction in all relevant CO2, temperature and pressure conditions*
- Factory calibration is intended for using sensor in narrower temperature range and does not include pressure information → measurements based on factory calibration are not as accurate as they can be under outdoor conditions when using an extended model*
- Meaningful reductions in network uncertainties following the application of a temperature-dependence correction and a resulting network instrument error of 1.6ppm CO2 or less**
- Uses application of temperature-dependence correction, which does not require to manually calibrate each sensor at the sensor site. In order to get greater network accuracy a higher-cost reference instrument can be used.**
- Network precision can be maintained at 1.3% even in locations without a high-cost reference instrument, by using the network median as a reference. However it is provided that there are at least 12 sites with small temperature dependencies.**
- Without a reference instrument, the network accuracy error increases relative to a network that utilizes a reference instrument by ~± 2ppm.**
- Additional methods for characterizing network scale uncertainties and site-to-site biases are described**
- Calibration is a one time step before releasing the sensor to the end user.
BEACO2N