Evaluation of an on-line methodology for measuring volatile organic compounds (VOC) fluxes by eddy-covariance with a PTR-TOF-Qi-MS
Résumé
Field scale flux measurements of volatile organic compounds (VOC) are
essential for improving our knowledge of VOC emissions from ecosystems.
Many VOCs are emitted from and deposited to ecosystems. Especially less
known, are crops which represent more than 50% of French terrestrial
surfaces. In this study, we evaluate a new on-line methodology for
measuring VOC fluxes by Eddy Covariance with a PTR-Qi-TOF-MS.
Measurements were performed at the ICOS FR-GRI site over a crop using a
30 m long high flow rate sampling line and an ultrasonic anemometer. A
Labview program was specially designed for acquisition and on-line
covariance calculation: Whole mass spectra ( 240000 channels) were
acquired on-line at 10 Hz and stored in a temporary memory. Every 5
minutes, the spectra were mass-calibrated and normalized by the primary
ion peak integral at 10 Hz. The mass spectra peaks were then retrieved
from the 5-min averaged spectra by withdrawing the baseline, determining
the resolution and using a multiple-peak detection algorithm. In order
to optimize the peak detection algorithm for the covariance, we
determined the covariances as the integrals of the peaks of the
vertical-air-velocity-fluctuation weighed-averaged-spectra. In other
terms, we calculate , were w is the vertical
component of the air velocity, Sp is the spectra, t is time, lag is the
decorrelation lag time and denotes an average. The lag time
was determined as the decorrelation time between w and the primary ion
(at mass 21.022) which integrates the contribution of all reactions of
VOC and water with the primary ion. Our algorithm was evaluated by
comparing the exchange velocity of water vapor measured by an open path
absorption spectroscopy instrument and the water cluster measured with
the PTRQi-TOF-MS. The influence of the algorithm parameters and lag
determination is discussed. This study was supported by the ADEME-CORTEA
COV3ER project (http://www6.inra.fr/cov3er).
Auteurs, date et publication :
Auteurs Benjamin Loubet , Pauline Buysse , Florence Lafouge , Raluca Ciuraru , Céline Decuq , Olivier Zurfluh
Date : 2017
Volume : 19
Pages : 16989