HAL Id: hal-02738941
https://hal.inrae.fr/hal-02738941
Submitted on 2 Jun 2020
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Two case studies of N2O measurements by eddy covariance during field campaigns: data analysis and
uncertainty sources.
Agnès Grossel, Jordan Bureau, Benjamin Loubet, Patricia Laville, Raia Silvia Massad, Catherine Hénault
To cite this version:
Agnès Grossel, Jordan Bureau, Benjamin Loubet, Patricia Laville, Raia Silvia Massad, et al.. Two case studies of N2O measurements by eddy covariance during field campaigns: data analysis and uncertainty sources.. InGOS International Conference, final meeting. Non–CO2 Greenhouse Gases, Sep 2015, Utrecht, Netherlands. 2015. �hal-02738941�
2 case studies of N2O measurements by eddy covariance during field campaigns: data analysis and uncertainty sources.
Agnès Grossel a, Jordan Bureau a, Benjamin Loubet b, Patricia Laville b, Raia Massad b, and Catherine Hénault a
aINRA, UR 0272 Science du sol, Centre de recherche d’Orléans, CS 40001 Ardon, 45075 Orléans cedex (France)
bINRA, UMR EcoSys, F-‐ 78850 Thiverval-‐Grignon (France).
Evaluations of N2O fluxes by the eddy covariance method remain challenging because of the high sensitivity and high frequency required in N2O concentration measurements. Two datasets from different field campaigns with the same QCL gas analyzer measuring N2O, H2O and CH4 by absorption spectroscopy (Aerodyne Research Inc.) were compared with the focus on signal quality control and flux error analysis. The first dataset was recorded from 6 to 27 June 2013 with a 2 m high mast over fertilized grasslands, during the inter-‐comparison INGOS campaign for N2O flux measurements at Easter Bush (Edinburgh, UK). The second dataset was recorded from 1 April to 18 May 2015 with a 15 m high mast within a cropped area mainly dedicated to cereals and rapeseed crops in Centre France. Both campaigns enabled to capture emissions following fertilizations. Offset drifts on the raw N2O mixing ratio signal were observed during the second campaign probably because the gas analyzer was housed in a simple vented box which could not fully dampen temperature variations.
Oppositely no drift was observed during the first campaign. We used a recursive running mean filter on raw signal (Mamarella et al. 2010) and the time constant needed for the filter was determined using Allan variance analysis. By this way, the artificial fluctuations of the estimated flux due to raw signal drift were successfully eliminated.
Mammarella, I., Werle, P., Pihlatie, M., Eugster, W., Haapanala, S., Kiese, R., ... & Vesala, T.
(2010). Biogeosciences, 7(2), 427-440.
