Abstract
The trace gas carbonyl sulphide (COS) has lately received growing interest in the eddy covariance (EC) community due to its potential to serve as an independent approach for constraining gross primary production and canopy stomatal conductance. Thanks to recent developments of fast-response high-precision trace gas analysers (e.g. quantum cascade laser absorption spectrometers (QCLAS)), a handful of EC COS flux measurements have been published since 2013. To date, however, a thorough methodological characterisation of QCLAS with regard to the requirements of the EC technique and the necessary processing steps has not been conducted. The objective of this study is to present a detailed characterization of the COS measurement with the Aerodyne QCLAS in the context of the EC technique, and to recommend best EC processing practices for those measurements. Data were collected from May to October 2015 at a temperate mountain grassland in Tyrol, Austria. Analysis of the Allan variance of high-frequency concentration measurements revealed sensor drift to occur under field conditions after an averaging time of around 50 s. We thus explored the use of two high-pass filtering approaches (linear detrending and recursive filtering) as opposed to block averaging and linear interpolation of regular background measurements for covariance computation. Experimental low-pass filtering correction factors were derived from a detailed cospectral analysis. The CO2 and H2O flux measurements obtained with the QCLAS were compared against those obtained with a closed-path infrared gas analyser. Overall, our results suggest small, but systematic differences between the various high-pass filtering scenarios with regard to the fraction of data retained in the quality control and flux magnitudes. When COS and CO2 fluxes are combined in the so-called ecosystem relative uptake rate, systematic differences between the high-pass filtering scenarios largely cancel out, suggesting that this relative metric represents a robust key parameter comparable between studies relying on different post-processing schemes.
Highlights
The need to understand human-induced climate change and in this context to understand the pathways and processes determining the global carbon cycle dynamics, triggered the increased use of the eddy covariance (EC) method for carbon dioxide (CO2) flux measurements and resulted in the establishment of the first flux measurement network, the EUROFLUX project, in 1996
The resulting lag times were slightly longer than nominal lag times calculated based on tube flow and dimensions (1.9 s), which has been found for other closed-path eddy covariance systems as well and likely reflects unaccounted volumes (e.g. quantum cascade laser spectrometers (QCLAS) cell, filters), horizontal sensor separation and the scalar response time (Massman, 2000)
Even though the number of published eddy covariance carbonyl sulfide (COS) flux measurements has increased significantly during the past few years (Asaf et al, 2013; Billesbach et al, 2014; Maseyk et al, 2014; Commane et al, 2015; Wehr et al, 2017), this is the first study to systematically examine the use of QCLAS instruments for making defensible COS flux measurements, the necessary processing steps and quality assurance and quality control (QA/QC) procedures, and to characterise the random flux uncertainty
Summary
The need to understand human-induced climate change and in this context to understand the pathways and processes determining the global carbon cycle dynamics, triggered the increased use of the eddy covariance (EC) method for carbon dioxide (CO2) flux measurements and resulted in the establishment of the first flux measurement network, the EUROFLUX project, in 1996. By partitioning the biosphere–atmosphere CO2 fluxes (net ecosystem exchange - NEE) into uptake (gross primary productivity – GPP) and release (ecosystem respiration – Reco), it is possible to quantify the two main processes underlying the NEE. To this end, eddy covariance CO2 flux partitioning algorithms are used.
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