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Evaluation of high resolution simulated and OMI retrieved tropospheric NO2 column densities over Southeastern Europe

dc.contributor.authorZyrichidou, I.
dc.contributor.authorKoukouli, M.E.
dc.contributor.authorBalis, D.S.
dc.contributor.authorKioutsioukis, I.
dc.contributor.authorPoupkou, A.
dc.contributor.authorKatragkou, E.
dc.contributor.authorMelas, D.
dc.contributor.authorBoersma, K.F.
dc.contributor.authorVan Roozendael, M.
dc.date2013
dc.date.accessioned2016-03-25T11:11:10Z
dc.date.available2016-03-25T11:11:10Z
dc.identifier.urihttps://orfeo.belnet.be/handle/internal/2895
dc.descriptionHigh resolution model estimates (10 × 10 km2) of tropospheric NO2 column amounts from the Comprehensive Air Quality Model (CAMx) for the Balkan Peninsula are compared with OMI/Aura measurements (13 × 24 km2 at nadir) for the year April 2009 to March 2010. The Balkan area contributes significantly to the NO2 burden in European air and so numerous urban, industrial and rural regions are studied aiming to investigate the consistency of both satellite retrievals and model predictions at high spatial resolution. It has already been shown that OMI can detect the tropospheric column of NO2 over polluted Balkan cities due to its fine horizontal resolution and instrument sensitivity (Zyrichidou et al., 2009). In this study the improved OMI DOMINO v2.0 satellite retrievals showed that over South-Eastern Europe the monthly mean NO2 tropospheric column density fluctuated between 2.0 and 5.7 ± 1.1 × 1015 molecules/cm2 over urban areas, 1.6–5.0 ± 0.7 × 1015 molecules/cm2 over large industrial complexes and 1.1–2.2 ± 0.4 × 1015 molecules/cm2 over rural areas for the year studied. The Comprehensive Air Quality Model with extensions (CAMx) version 4.40 is a publicly available open-source computer modeling system for the integrated assessment of gaseous and particulate air pollution. The anthropogenic emissions used in CAMx for the Greek domain being studied were compiled employing bottom-up approaches (road transport sector, off-road machinery, etc.) as well as other national registries and international databases. The rest of the Balkan domain has natural and anthropogenic emissions based on the TNO emission inventory of 2003. The high-resolution CAMx simulations reveal consistent spatial and temporal patterns with the OMI/Aura data. The annual spatial correlation coefficient between OMI and CAMx computed in this high spatial resolution analysis is of the order of 0.6, somewhat improved over those estimated in Zyrichidou et al. (2009) (R ≈ 0.5). However, in such a validation study it is important to take into account the averaging kernel (AK) information in order to achieve the creation of comparable data sets. Minor differences are found for area-averaged model columns with and without applying the kernel, which shows that the impact of limiting the effect of the a priori profile on the comparison is on average small. The main aim of the paper, which was to evaluate OMI retrieved and high resolution simulated tropospheric NO2 column densities over South-Eastern Europe and to assess the use of the averaging kernels, is achieved and the two data sources are being employed further in an inverse emission inventory creation study ( Zyrichidou et al., in preparation).
dc.languageeng
dc.titleEvaluation of high resolution simulated and OMI retrieved tropospheric NO2 column densities over Southeastern Europe
dc.typeArticle
dc.subject.frascatiEarth and related Environmental sciences
dc.audienceScientific
dc.subject.freeAir quality models
dc.subject.freeAnthropogenic emissions
dc.subject.freeBottom up approach
dc.subject.freeColumn amount
dc.subject.freeColumn density
dc.subject.freeComprehensive air quality model with extensions
dc.subject.freeComputer modeling
dc.subject.freeData sets
dc.subject.freeData-sources
dc.subject.freeEmission inventories
dc.subject.freeHigh resolution
dc.subject.freeHigh spatial resolution
dc.subject.freeHigh-resolution models
dc.subject.freeHorizontal resolution
dc.subject.freeIndustrial complex
dc.subject.freeIntegrated assessment
dc.subject.freeModel prediction
dc.subject.freeModel simulation
dc.subject.freeOff-road machinery
dc.subject.freeOpen-source
dc.subject.freeParticulate air pollution
dc.subject.freeRoad transport sectors
dc.subject.freeRural regions
dc.subject.freeSatellite measurements
dc.subject.freeSatellite retrieval
dc.subject.freeSouth Eastern Europe
dc.subject.freeSpatial correlations
dc.subject.freeTemporal pattern
dc.subject.freeTropospheric columns
dc.subject.freeTropospheric nitrogen dioxide
dc.subject.freeTropospheric NO
dc.subject.freeUrban areas
dc.subject.freeValidation study
dc.subject.freeAir quality
dc.subject.freeNitrogen oxides
dc.subject.freeRural areas
dc.subject.freeTroposphere
dc.subject.freeComputer simulation
dc.subject.freeair quality
dc.subject.freeatmospheric chemistry
dc.subject.freeatmospheric modeling
dc.subject.freenitrogen dioxide
dc.subject.freesatellite imagery
dc.subject.freetroposphere
dc.subject.freeBalkans
dc.subject.freeEurope
dc.source.titleAtmospheric Research
dc.source.volume122
dc.source.page55-66
Orfeo.peerreviewedYes
dc.identifier.doi10.1016/j.atmosres.2012.10.028
dc.identifier.scopus2-s2.0-84871144332


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