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  • 1
    In: Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 16, No. 24 ( 2023-12-14), p. 5977-5994
    Abstract: Abstract. The identification of spikes (i.e., short and high variability in the measured signals due to very local emissions occurring in the proximity of a measurement site) is of interest when using continuous measurements of atmospheric greenhouse gases (GHGs) in different applications like the determination of long-term trends and/or spatial gradients, inversion experiments devoted to the top-down quantification of GHG surface–atmosphere fluxes, the characterization of local emissions, or the quality control of GHG measurements. In this work, we analyzed the results provided by two automatic spike identification methods (i.e., the standard deviation of the background (SD) and the robust extraction of baseline signal (REBS)) for a 2-year dataset of 1 min in situ observations of CO2, CH4 and CO at 10 different atmospheric sites spanning different environmental conditions (remote, continental, urban). The sensitivity of the spike detection frequency and its impact on the averaged mole fractions on method parameters was investigated. Results for both methods were compared and evaluated against manual identification by the site principal investigators (PIs). The study showed that, for CO2 and CH4, REBS identified a larger number of spikes than SD and it was less “site-sensitive” than SD. This led to a larger impact of REBS on the time-averaged values of the observed mole fractions for CO2 and CH4. Further, it could be shown that it is challenging to identify one common algorithm/configuration for all the considered sites: method-dependent and setting-dependent differences in the spike detection were observed as a function of the sites, case studies and considered atmospheric species. Neither SD nor REBS appeared to provide a perfect identification of the spike events. The REBS tendency to over-detect the spike occurrence shows limitations when adopting REBS as an operational method to perform automatic spike detection. REBS should be used only for specific sites, mostly affected by frequent very nearby local emissions. SD appeared to be more selective in identifying spike events, and the temporal variabilities in CO2, CH4 and CO were more consistent with those of the original datasets. Further activities are needed for better consolidating the fitness for purpose of the two proposed methods and to compare them with other spike detection techniques.
    Type of Medium: Online Resource
    ISSN: 1867-8548
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2023
    detail.hit.zdb_id: 2505596-3
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  • 2
    In: Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 14, No. 1 ( 2021-01-05), p. 89-116
    Abstract: Abstract. The Integrated Carbon Observation System (ICOS) is a pan-European research infrastructure which provides harmonized and high-precision scientific data on the carbon cycle and the greenhouse gas budget. All stations have to undergo a rigorous assessment before being labeled, i.e., receiving approval to join the network. In this paper, we present the labeling process for the ICOS atmosphere network through the 23 stations that were labeled between November 2017 and November 2019. We describe the labeling steps, as well as the quality controls, used to verify that the ICOS data (CO2, CH4, CO and meteorological measurements) attain the expected quality level defined within ICOS. To ensure the quality of the greenhouse gas data, three to four calibration gases and two target gases are measured: one target two to three times a day, the other gases twice a month. The data are verified on a weekly basis, and tests on the station sampling lines are performed twice a year. From these high-quality data, we conclude that regular calibrations of the CO2, CH4 and CO analyzers used here (twice a month) are important in particular for carbon monoxide (CO) due to the analyzer's variability and that reducing the number of calibration injections (from four to three) in a calibration sequence is possible, saving gas and extending the calibration gas lifespan. We also show that currently, the on-site water vapor correction test does not deliver quantitative results possibly due to environmental factors. Thus the use of a drying system is strongly recommended. Finally, the mandatory regular intake line tests are shown to be useful in detecting artifacts and leaks, as shown here via three different examples at the stations.
    Type of Medium: Online Resource
    ISSN: 1867-8548
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2021
    detail.hit.zdb_id: 2505596-3
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  • 3
    In: Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 14, No. 9 ( 2021-09-17), p. 6119-6135
    Abstract: Abstract. We present a statistical framework to identify regional signals in station-based CO2 time series with minimal local influence. A curve-fitting function is first applied to the detrended time series to derive a harmonic describing the annual CO2 cycle. We then combine a polynomial fit to the data with a short-term residual filter to estimate the smoothed cycle and define a seasonally adjusted noise component, equal to 2 standard deviations of the smoothed cycle about the annual cycle. Spikes in the smoothed daily data which surpass this ±2σ threshold are classified as anomalies. Examining patterns of anomalous behavior across multiple sites allows us to quantify the impacts of synoptic-scale atmospheric transport events and better understand the regional carbon cycling implications of extreme seasonal occurrences such as droughts.
    Type of Medium: Online Resource
    ISSN: 1867-8548
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2021
    detail.hit.zdb_id: 2505596-3
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  • 4
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 22, No. 20 ( 2022-10-17), p. 13243-13268
    Abstract: Abstract. We present a novel high-resolution inverse modelling system (“FLEXVAR”) based on FLEXPART-COSMO back trajectories driven by COSMO meteorological fields at 7 km×7 km resolution over the European COSMO-7 domain and the four-dimensional variational (4DVAR) data assimilation technique. FLEXVAR is coupled offline with the global inverse modelling system TM5-4DVAR to provide background mole fractions (“baselines”) consistent with the global observations assimilated in TM5-4DVAR. We have applied the FLEXVAR system for the inverse modelling of European CH4 emissions in 2018 using 24 stations with in situ measurements, complemented with data from five stations with discrete air sampling (and additional stations outside the European COSMO-7 domain used for the global TM5-4DVAR inversions). The sensitivity of the FLEXVAR inversions to different approaches to calculate the baselines, different parameterizations of the model representation error, different settings of the prior error covariance parameters, different prior inventories, and different observation data sets are investigated in detail. Furthermore, the FLEXVAR inversions are compared to inversions with the FLEXPART extended Kalman filter (“FLExKF”) system and with TM5-4DVAR inversions at 1∘×1∘ resolution over Europe. The three inverse modelling systems show overall good consistency of the major spatial patterns of the derived inversion increments and in general only relatively small differences in the derived annual total emissions of larger country regions. At the same time, the FLEXVAR inversions at 7 km×7 km resolution allow the observations to be better reproduced than the TM5-4DVAR simulations at 1∘×1∘. The three inverse models derive higher annual total CH4 emissions in 2018 for Germany, France, and BENELUX compared to the sum of anthropogenic emissions reported to UNFCCC and natural emissions estimated from the Global Carbon Project CH4 inventory, but the uncertainty ranges of top-down and bottom-up total emission estimates overlap for all three country regions. In contrast, the top-down estimates for the sum of emissions from the UK and Ireland agree relatively well with the total of anthropogenic and natural bottom-up inventories.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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