ALBERT

Description: Accurate multi-point monitoring systems are required to derive atmospheric measurements of greenhouse gas concentrations both for the calculation of surface fluxes with inversion transport models and for the estimation of non-turbulent components of the mass balance equation (i.e. advection and storage fluxes) at eddy covariance sites. When a single analyser is used to monitor multiple sampling points, the deployment of buffer volumes (BV) along sampling lines can reduce the uncertainty due to the discrete temporal sampling of the signal. In order to optimize the use of buffer volumes we explored various setups by simulating their effect on time series of high-frequency CO2 concentration collected at three Fluxnet sites. Besides, we proposed a novel scheme to calculate half hourly weighted averages from discrete point samples, accounting for the probabilistic fraction of the signal generated in the averaging period. Results show that the use of BV with the new averaging scheme reduces the mean absolute errors (MAE) up to 80 % compared to set-up without BV and up to 60 % compared to the case with BV and a standard, non-weighted averaging scheme. The MAE of CO2 concentration measurements was observed to depend on the variability of the concentration field and on the size of BV, which therefore have to be carefully dimensioned. The optimal volume size depends on two main features of the instrumental setup: the number of measurement points and the time needed to sample at one point (i.e. line purging plus sampling time). A linear and consistent relationship was observed at all sites between the sampling frequency, which summarizes the two features mentioned above, and the renewal frequency associated to the volume. Ultimately, this empirical relationship can be applied to estimate the optimal volume size according to the technical specifications of the sampling system.