Impact of CO2 Storage Flux Sampling Uncertainty on Net Ecosystem Exchange Measured by Eddy Covariance
Abstract
Most of the carbon budget studies based on eddy covariance (EC) measurements over tall crops and forest quantify the CO2 net ecosystem exchange (NEE) by commonly summing the flux obtained by EC (FC) and the storage flux (SC). SC is the rate of change of CO2 concentration, or any other scalar, within the control volume underneath the EC measurement level. A single profile of concentrations is commonly assumed to be sufficient for the estimation of SC and thus representative of the average condition in the whole control volume, although there are stations were a single point measurement is used (assuming a constant gradient of concentration). We use the experimental dataset collected during the ADVEX campaign in which turbulent and non-turbulent fluxes were measured in three forests by the simultaneous use of five towers/profiles, to evaluate both the uncertainty of SC which derives from an insufficient sampling of CO2 variability and its impact on concurrent NEE estimates. Results showed that different measurement methods may produce substantially different SC flux estimates which, in some cases, involve a significant underestimation of SC at a half-hourly time scales (and consequently an error in the NEE that is however minor when integrated over long term sums). A compromise between measurement quality and system complexity is a measuring system that uses a single vertical profile of which the CO2 sampled at the 3 lowest levels is averaged with CO2 sampled at a certain distance and at the same height. This improves the horizontal representativeness and reduces the (proportional) bias to 2-10% in such ecosystems. In this context, the recent technological improvement in the production of sensibly cheaper sensors can help reducing the uncertainty. The drawback of a minor measurement performance which characterize such sensors, may be reduced by the massive use of several units, so that to improve the spatial representativity of the sampling. First tests on the applicability a number of low-cost sensors show promising results.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.B33I2783N
- Keywords:
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- 0414 Biogeochemical cycles;
- processes;
- and modeling;
- BIOGEOSCIENCESDE: 0426 Biosphere/atmosphere interactions;
- BIOGEOSCIENCESDE: 0428 Carbon cycling;
- BIOGEOSCIENCESDE: 0438 Diel;
- seasonal;
- and annual cycles;
- BIOGEOSCIENCES