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

Abstract

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) on-board the Sentinel-5 Precursor satellite (launched on 13 October 2017) is a nadir-viewing spectrometer measuring reflected sunlight in the ultraviolet, visible, near-infrared, and shortwave infrared spectral ranges. The measured spectra are used to retrieve total columns of trace gases, including nitrogen dioxide (NO2). For ground validation of these satellite measurements, Pandora spectrometers, which retrieve high-quality NO2 total columns via direct-sun measurements, are widely used. In this study, Pandora NO2 measurements made at three sites located in or north of the Greater Toronto Area (GTA) are used to evaluate the TROPOMI NO2 data products, including standard Royal Netherlands Meteorological Institute (KNMI) tropospheric and stratospheric NO2 data product and a TROPOMI research data product developed by Environment and Climate Change Canada (ECCC) using a high-resolution regional air quality forecast model (used in the air mass factor calculation). It is found that these current TROPOMI tropospheric NO2 data products (standard and ECCC) met the TROPOMI design bias requirement. Using the statistical uncertainty estimation method, the estimated TROPOMI upper limit precision falls below the design requirement at a rural site, but above in the other two urban and suburban sites. The Pandora instruments are found to have sufficient precision to perform TROPOMI validation work. In addition to the traditional satellite validation method (i.e., pairing ground-based measurements with satellite measurements closest in time and space), we analyzed TROPOMI pixels located upwind and downwind from the Pandora site. This makes it possible to improve the statistics and better interpret the high-spatial-resolution measurements made by TROPOMI. By using this wind-based validation technique, the number of coincident measurements can be increased by about a factor of five. Using this larger number of coincident measurements, this work shows that both TROPOMI and Pandora instruments can reveal detailed spatial patterns (i.e., horizontal distributions) of local and transported NO2 emissions, which can be used to evaluate regional air quality changes. The TROPOMI ECCC NO2 research data product shows improved agreement with Pandora measurements compared to the TROPOMI standard tropospheric NO2 data product, demonstrating benefits from the high-resolution regional air quality forecast model.

Assessment of the TROPOMI tropospheric NO<sub>2</sub> product based on airborne APEX observations

“…reference observations at higher resolution and this is consistent with the findings in other studies Ialongo et al, 2019;Zhao et al, 2019;Dimitropoulou et al, 2020;Verhoelst et al, 2020).…”

“…However, highly polluted areas typically exhibit strong NO2 vertical and horizontal gradients (see e.g. Dieudonné et al, 2013;Ialongo et al, 2019;Zhao et al, 2019;Dimitropoulou https://doi.org/10.5194/amt-2020-148 Preprint. Discussion started: 29 June 2020 c Author(s) 2020.…”

Evaluating Sentinel-5P TROPOMI tropospheric NO<sub>2</sub> column densities with airborne and Pandora spectrometers near New York City and Long Island Sound

“…Toronto, Canada (Zhao et al, 2019), Paris, France (Lorente et al, 2019), and polluted scenes ( > 10´10 15 molecules cm -2 ) near…”

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“…Recent studies using Pandora data to evaluate TROPOMI NO2 products have used different coincidence criteria in terms of the temporal window and statistics applied to Pandora data. Griffin et al (2019) averaged Pandora data within ± 30 min window of the S5P overpass, similar to the current methodology but instead here the median is used to limit possible influence of isolated small-scale plumes that TROPOMI is likely not sensitive to. Ialongo et al (2020) and Zhao et al (2019) 75 used a smaller temporal window of ± 10 minutes, though they used the average and closest coincidence, respectively.…”

“…Griffin et al (2019) averaged Pandora data within ± 30 min window of the S5P overpass, similar to the current methodology but instead here the median is used to limit possible influence of isolated small-scale plumes that TROPOMI is likely not sensitive to. Ialongo et al (2020) and Zhao et al (2019) 75 used a smaller temporal window of ± 10 minutes, though they used the average and closest coincidence, respectively. Unlike in airborne-Pandora comparisons, only considering Pandora coincidences where its TrVC does not vary more than 30% within a ± 30 min window does not improve r 2 , but does show an increase in slope.…”