Comparison of TROPOMI/Sentinel-5 Precursor NO<sub>2</sub> observations with ground-based measurements in Helsinki

Abstract

Abstract. We present a comparison between satellite-based TROPOMI (TROPOspheric Monitoring Instrument) NO2 products and ground-based observations in Helsinki (Finland). TROPOMI NO2 total (summed) columns are compared with the measurements performed by the Pandora spectrometer between April and September 2018. The mean relative and absolute bias between the TROPOMI and Pandora NO2 total columns is about 10 % and 0.12×1015 molec. cm−2 respectively. The dispersion of these differences (estimated as their standard deviation) is 2.2×1015 molec. cm−2. We find high correlation (r = 0.68) between satellite- and ground-based data, but also that TROPOMI total columns underestimate ground-based observations for relatively large Pandora NO2 total columns, corresponding to episodes of relatively elevated pollution. This is expected because of the relatively large size of the TROPOMI ground pixel (3.5×7 km) and the a priori used in the retrieval compared to the relatively small field-of-view of the Pandora instrument. On the other hand, TROPOMI slightly overestimates (within the retrieval uncertainties) relatively small NO2 total columns. Replacing the coarse a priori NO2 profiles with high-resolution profiles from the CAMS chemical transport model improves the agreement between TROPOMI and Pandora total columns for episodes of NO2 enhancement. When only the low values of NO2 total columns or the whole dataset are taken into account, the mean bias slightly increases. The change in bias remains mostly within the uncertainties. We also analyse the consistency between satellite-based data and in situ NO2 surface concentrations measured at the Helsinki–Kumpula air quality station (located a few metres from the Pandora spectrometer). We find similar day-to-day variability between TROPOMI, Pandora and in situ measurements, with NO2 enhancements observed during the same days. Both satellite- and ground-based data show a similar weekly cycle, with lower NO2 levels during the weekend compared to the weekdays as a result of reduced emissions from traffic and industrial activities (as expected in urban sites). The TROPOMI NO2 maps reveal also spatial features, such as the main traffic ways and the airport area, as well as the effect of the prevailing south-west wind patterns. This is one of the first works in which TROPOMI NO2 retrievals are validated against ground-based observations and the results provide an early evaluation of their applicability for monitoring pollution levels in urban sites. Overall, TROPOMI retrievals are valuable to complement the ground-based air quality data (available with high temporal resolution) for describing the spatio-temporal variability of NO2, even in a relatively small city like Helsinki.

Satellite-detected tropospheric nitrogen dioxide and spread of SARS-CoV-2 infection in Northern Italy

“…Prevalence rate (per 100,000) NO 2 levels (μmol/m 2 ) levels as a proxy for overall air pollution. This metric was closely associated with ground levels of this contaminant in a validation study in the study area as well as in other European urban areas (Ialongo et al, 2020;Lorente et al, 2019). In vitro studies have shown that NO 2 can alter expression and synthesis of pro-inflammatory mediators in human bronchial cells (Bayram et al, 2001;Blomberg et al, 1997;Blomberg et al, 1999;Devalia et al, 1993;Mirowsky et al, 2016), thus increasing inflammation and hyperresponsiveness of epithelial cells.…”

Assessment of the quality of TROPOMI high-spatial-resolution NO<sub>2</sub> data products in the Greater Toronto Area

“…To validate the satellite measurements, coincident groundbased data are required. The coincidence criteria are normally composed of spatial, temporal and quality control criteria (e.g., Boersma et al, 2018;Drosoglou et al, 2017;Griffin et al, 2019;Irie et al, 2008;Toohey and Strong, 2007). For example, in Zhao et al (2019b), the coincidence criteria used to pair ground-based observations (Pandora) and OMI data include (1) the nearest (in time) measurement that was within ±30 min of the OMI overpass time, (2) the closest OMI ground pixel (having a distance of less than 20 km from the ground pixel centre to the location of the Pandora instrument), and (3) cloud fraction < = 0.3 (the effective geometric cloud fraction as determined by the OMCLDO2 algorithm), and only high-quality OMI data are used (VcdQual-ityFlags = 0) (Celarier et al, 2016).…”

“…Total vertical column NO 2 can be measured by groundbased UV-visible remote sensing instruments using directsun, zenith-sky, or off-axis spectroscopy techniques (Cede et al, 2006;Drosoglou et al, 2017;Herman et al, 2009;Lee et al, 1994;Noxon, 1975;Piters et al, 2012;Roscoe et al, 2010;Vaughan et al, 1997). These measurements are of high quality and good precision and have been widely used for atmospheric chemistry studies (e.g., Adams et al, 2012;Hendrick et al, 2014) and satellite validations (e.g., Celarier et al, 2008;Drosoglou et al, 2018;Irie et al, 2008;Wenig et al, 2008). Among all these different viewing geometries, direct-sun measurements are of high accuracy and are not dependent on radiative transfer models (RTMs) to calculate air mass factors (AMFs) (Herman et al, 2009) or on knowledge of other atmospheric constituents.…”

Shipborne MAX-DOAS measurements for validation of TROPOMI NO&lt;sub&gt;2&lt;/sub&gt; products

“…Tropospheric NO 2 is mostly produced at high temperatures in combustion processes but also in soil microbial process and lightning events. In the stratosphere, NO 2 is an ozone-depleting substance produced primarily from the oxidation of nitrous oxide (N 2 O) (Crutzen, 1970;Johnston, 1971;Seinfeld and Pandis, 2006). NO x can also suppress ozone depletion by converting reactive chlorine and hydrogen compounds into unreactive reservoir species (Murphy et al, 1993).…”