Comparison of S5P/TROPOMI inferred NO2 surface concentrations with
in-situ measurements over Central Europe
Pseftogkas, A., Koukouli, M., Segers, A., Manders, A., Van Geffen, J.,
Balis, D., Meleti, C., Stavrakou, T. and Eskes, H.: 2022,
Remote Sensing 15, 4886, 24 pp.
Abstract
The aim of this paper is to evaluate the surface concentration of nitrogen
dioxide (NO2) inferred from the Sentinel-5 Precursor Tropospheric Monitoring
Instrument (S5P/TROPOMI) NO2 tropospheric column densities over Central
Europe for two time periods, summer 2019 and winter 2019-2020. Simulations
of the NO2 tropospheric vertical column densities and surface concentrations
from the Long-Term Ozone Simulation-European Operational Smog (LOTOS-EUROS)
chemical transport model are also applied in the methodology. More than two
hundred in situ air quality monitoring stations, reporting to the European
Environment Agency (EEA) air quality database, are used to carry out
comparisons with the model simulations and the spaceborne inferred surface
concentrations. Stations are separated into seven types (urban traffic,
suburban traffic, urban background, suburban background, rural background,
suburban industrial and rural industrial) in order to examine the strengths
and shortcomings of the different air quality markers, namely the NO2
vertical column densities and NO2 surface concentrations. S5P/TROPOMI NO2
surface concentrations are inferred by multiplying the fraction of the
satellite and model NO2 vertical column densities with the model surface
concentrations. The estimated inferred TROPOMI NO2 surface concentrations
are examined further with the altering of three influencing factors: the
model vertical leveling scheme, the versions of the TROPOMI NO2 data and the
air mass factors applied to the satellite and model NO2 vertical column
densities. Overall, the inferred TROPOMI NO2 surface concentrations show a
better correlation with the in situ measurements for both time periods and
all station types, especially for the industrial stations (R > 0.6) in
winter. The calculated correlation for background stations is moderate for
both periods (R~0.5 in summer and R > 0.5 in winter), whereas for traffic
stations it improves in the winter (from 0.20 to 0.50). After the
implementation of the air mass factors from the local model, the bias is
significantly reduced for most of the station types, especially in winter
for the background stations, ranging from +0.49% for the urban background to
+10.37% for the rural background stations. The mean relative bias in winter
between the inferred S5P/TROPOMI NO2 surface concentrations and the
ground-based measurements for industrial stations is about -15%, whereas for
traffic urban stations it is approximately -25%. In summer, biases are
generally higher for all station types, especially for the traffic stations
(~-75%), ranging from -54% to -30% for the background and industrial
stations.
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created: 8 June 2022
last modified: 8 August 2022