Intercomparison of SCIAMACHY nitrogen dioxide observations, in situ measurements and air quality modeling results over Western Europe

Abstract

[1] The Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) satellite spectrometer provides detailed information on the nitrogen dioxide (NO 2 ) content in the planetary boundary layer. NO 2 tropospheric column retrievals of SCIAMACHY and its predecessor Global Ozone Monitoring Experiment are characterized by errors of the order of 40%. We present here a new SCIAMACHY tropospheric retrieval data set for the year 2003. The cloud free satellite observations are compared to surface measurements and simulations over western Europe performed with the regional air-quality model CHIMERE. The model has a resolution of 50 km similar to the satellite observations. For these comparisons, averaging kernels are applied to the collocated model profiles to remove the dependency of the comparison on a priori NO 2 profile information used in the retrieval. The consistency of both SCIAMACHY and CHIMERE outputs over sites where surface measurements are available allows us to be confident in evaluation of the model over large areas not covered by surface observations. CHIMERE underestimates surface NO 2 concentrations for urban and suburban stations which we mainly attribute to the low representativeness of point observations. No such bias is found for rural locations. The yearly average SCIAMACHY and CHIMERE spatial NO 2 distributions show a high degree of quantitative agreement over rural and urban sites: a bias of 5% (relative to the retrievals) and a correlation coefficient of 0.87 (n = 2003). On a seasonal basis, biases are smaller than 20% and correlation coefficients are larger than 0.75. Spatial correlations between both the model and satellite columns and the European Monitoring and Evaluation Program (EMEP) emission inventory are high in summer (r = 0.74, n = 1779) and low in winter (r = 0.48, n = 1078), related to seasonal changes in lifetime and transport. On the other hand, CHIMERE and SCIAMACHY columns are mutually consistent in summer (r = 0.82) and in winter (r = 0.79). This shows that CHIMERE simulates the transport and chemical processes with a reasonable accuracy. The NO 2 columns show a high daily variability. The daily NO 2 pollution plumes observed by SCIAMACHY are often well described by CHIMERE both in extent and in location. This result demonstrates the capabilities of a satellite instrument such as SCIAMACHY to monitor the NO 2 concentrations over large areas on a daily basis. It provides evidence that present and future satellite missions, in combination with CTM and surface data, will contribute to improve quantitative air quality analyses at a continental scale.

SCIAMACHY formaldehyde observations: constraint for isoprene emission estimates over Europe?

“…The model is also used for forecasts of pollutant levels as part of the French national air pollution forecasting system, Prev'Air (www.prevair.org). CHIMERE has been extensively validated with surface and airborne measurements for the different scales (Schmidt et al, 2001;Blond and Vautard, 2004;Menut et al, 2000;Vautard et al, 2003;Blond et al, 2007;Honoré et al, 2008). As an example, the averaged bias for daily ozone maxima over Europe is smaller than 10% (Honoré et al, 2008).…”

Recent satellite-based trends of tropospheric nitrogen dioxide over large urban agglomerations worldwide

“…The impact of topography on SCIAMACHY NO 2 retrievals was investigated by Schaub et al (2007) who found errors of up to 40 % over very complex terrain. Blond et al (2007) intercompared SCIAMACHY-based NO 2 retrievals with in situ station observations over Europe and found biases of less than 5 % and 20 % for annual and seasonal averages, respectively.…”

Comparison of OMI NO<sub>2</sub> tropospheric columns with an ensemble of global and European regional air quality models

“…We have selected 17 rural stations as their measurements are considered most representative for the regions comparable to the coinciding model grid (Blond et al, 2007). The corresponding model results have been interpolated in space and time to these measurement sites.…”

“…It highlighted the differences in the models, but also showed significant differences between the retrieval algorithms. A more detailed analysis on a 0.5 • grid for a regional model (CHIMERE) using the SCIAMACHY NO 2 data and surface observations was presented by Blond et al (2007). In these studies some of the differences between models as well as differences of models compared to NO 2 retrievals remained unclarified.…”