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Evaluating 4 years of atmospheric ammonia (NH 3 ) over Europe using IASI satellite observations and LOTOS‐EUROS model results
Author(s) -
Van Damme M.,
Wichink Kruit R. J.,
Schaap M.,
Clarisse L.,
Clerbaux C.,
Coheur P.F.,
Dammers E.,
Dolman A. J.,
Erisman J. W.
Publication year - 2014
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2014jd021911
Subject(s) - environmental science , satellite , climatology , spatial variability , meteorology , atmospheric sciences , geography , geology , statistics , mathematics , aerospace engineering , engineering
Monitoring ammonia (NH 3 ) concentrations on a global to regional scale is a challenge. Due to the limited availability of reliable ground‐based measurements, the determination of NH 3 distributions generally relies on model calculations. Novel remotely sensed NH 3 burdens provide valuable insights to complement traditional assessments for clear‐sky conditions. This paper presents a first quantitative comparison between Atmospheric Sounding Interferometer (IASI) satellite observations and LOTOS‐EUROS model results over Europe and Western Russia. A methodology to account for the variable retrieval sensitivity of the measurements is described. Four years of data (2008–2011) highlight three main agricultural hot spot areas in Europe: the Po Valley, the continental part of Northwestern Europe, and the Ebro Valley. The spatial comparison reveals a good overall agreement of the NH 3 distributions not only in these source regions but also over remote areas and over sea when transport is observed. On average, the measured columns exceed the modeled ones, except for a few cases. Large discrepancies over several industrial areas in Eastern Europe and Russia point to underestimated emissions in the underlying inventories. The temporal analysis over the three hot spot areas reveals that the seasonality is well captured by the model when the lower sensitivity of the satellite measurements in the colder months is taken into account. Comparison of the daily time series indicates possible misrepresentations of the timing and magnitude of the emissions. Finally, specific attention to biomass burning events shows that modeled plumes are less spread out than the observed ones. This is confirmed for the 2010 Russian fires with a comparison using in situ observations.