EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Influence of sensor type on the error of automatic chamber derived CO2 fluxes and gap-filled emission estimates

Katja Kramp1, Shrijana Vaidya1, Marten Schmidt1, Peter Rakowski2, Norbert Bonk2, Robert Buddrus2, Gernot Verch2, Michael Sommer3,4, Jürgen Augustin1, and Mathias Hoffmann1
Katja Kramp et al.
  • 1Leibniz Center for Agricultural Landscape Research (ZALF), working group for Isotope Biogeochemistry and Gas Fluxes, Muencheberg, Germany
  • 2Leibniz Center for Agricultural Landscape Research (ZALF), Research Station, Prenzlau, Germany
  • 3University of Potsdam, Institute of Environmental Science and Geography, 14476 Potsdam, Germany
  • 4Leibniz Center for Agricultural Landscape Research (ZALF), working group for Landscape Pedology, 15374 Müncheberg, Germany

Improved agricultural practices are considered as one of the potential solutions for mitigating global climate change. However, agricultural used landscapes are complex and their function as source and sink of greenhouse gases like CO2, CH4, and N2O might differ substantially in time and space. Hence, accurate and precise information on the complex spatio-temporal gas flux pattern is needed to evaluate the effects/benefits of new agricultural practices aiming towards increasing soil organic carbon. Automatic chamber measurements are increasingly used in agricultural systems to determine emissions of greenhouse gases as well as the net ecosystem C balance (NECB). While the eddy covariance (EC) technique remains to be the most common method at field scale, automated chamber measurements might close a gap, by detecting small-scale spatial emission patterns, while still compromising a sufficient temporal resolution. Infrared gas analysers (IRGAs) have been available for decades and helped to facilitate CO2 measurements substantially. In addition, further technical progress resulted in the development of multigas analysers, which are able to measure not only CO2, but also CH4, N2O, as well as their isotopes. However, most of these analysers are rather cost-intensive and many of them are primary designed for use in the laboratory.

Here, we compare CO2 fluxes and derived emission estimates, obtained using a widely applied IRGA (LI-850 CO2/H2O, Licor, Germany) with results of a new, medium cost, CO2, CH4, and N2O gas analyser (ProCeas GENERAL, AP2E, France). Two of both sensors were mounted on a novel robotic chamber system (“CarboCrane”), which was installed in 2019 at an undulating summit position of the hummocky ground moraine landscape of NE Germany. The system is comprised of a gantry crane mounted on two tracks (110 m) transporting the sensors and two transparent closed chambers. Measurements of the net CO2 exchange were performed by moving the system along the tracks with each chamber along one half of the covered area. Altogether, 36 measurement plots have been established. On each of these plots, an area for net CO2 exchange measurement has been set up by inserting round iron frames (diameter=1.59 m) 5 cm deep into the soil on which the transparent chambers were deployed for measurements. CO2 fluxes were determined by measuring the development of chamber headspace CO2 concentrations (4 sec frequency; measurements of both sensors in parallel) over chamber deployment time (7 min; see 2.5) in a flow-through non-steady-state (FT-NSS) mode (Livingston and Hutchinson, 1995). CO2 fluxes and emission estimates were derived for all four sensors for a test period of three month (April – June 2021) at six plots, covered with winter rye situated at a mineral fertilized, non-eroded Calcic Luvisol. To guarantee an enhanced variability in measured CO2 fluxes, the six measured plots divide into topsoil diluted and non-diluted treatments. Our results show in general a great consistency between the results delivered by both sensors and support the assumption of a rather small error fraction of the sensor type for both, the calculated CO2 flux and the emission estimates based on it.

How to cite: Kramp, K., Vaidya, S., Schmidt, M., Rakowski, P., Bonk, N., Buddrus, R., Verch, G., Sommer, M., Augustin, J., and Hoffmann, M.: Influence of sensor type on the error of automatic chamber derived CO2 fluxes and gap-filled emission estimates, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2175,, 2022.