Nitrogen dioxide (NO₂) is one of the main data products measured by the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (S5P) satellite, which combines a high signal-to-noise ratio with daily global coverage and high spatial resolution. TROPOMI provides a valuable source of information to monitor emissions from local sources such as power plants, industry, cities, traffic and ships, and variability of these sources in time. Validation exercises of NO₂ v1.2–v1.3 data, however, have revealed that TROPOMI's tropospheric vertical column densities (VCDs) are too low by up to 50 % over highly polluted areas. These findings are mainly attributed to biases in the cloud pressure retrieval, the surface albedo climatology and the low resolution of the a priori profiles derived from global simulations of the TM5-MP chemistry model. This study describes improvements in the TROPOMI NO₂ retrieval leading to version v2.2, operational since 1 July 2021. Compared to v1.x, the main changes are the following. (1) The NO₂-v2.2 data are based on version-2 level-1b (ir)radiance spectra with improved calibration, which results in a small and fairly homogeneous increase in the NO₂ slant columns of 3 % to 4 %, most of which ends up as a small increase in the stratospheric columns. (2) The cloud pressures are derived with a new version of the FRESCO cloud retrieval already introduced in NO₂-v1.4, which led to a lowering of the cloud pressure, resulting in larger tropospheric NO₂ columns over polluted scenes with a small but non-zero cloud coverage. (3) For cloud-free scenes a surface albedo correction is introduced based on the observed reflectance, which also leads to a general increase in the tropospheric NO₂ columns over polluted scenes of order 15 %. (4) An outlier removal was implemented in the spectral fit, which increases the number of good-quality retrievals over the South Atlantic Anomaly region and over bright clouds where saturation may occur. (5) Snow/ice information is now obtained from ECMWF weather data, increasing the number of valid retrievals at high latitudes. On average the NO₂-v2.2 data have tropospheric VCDs that are between 10 % and 40 % larger than the v1.x data, depending on the level of pollution and season; the largest impact is found at mid and high latitudes in wintertime. This has brought these tropospheric NO₂ closer to Ozone Monitoring Instrument (OMI) observations. Ground-based validation shows on average an improvement of the negative bias of the stratospheric (from −6 % to −3 %), tropospheric (from −32 % to −23 %) and total (from −12 % to −5 %) columns. For individual measurement stations, however, the picture is more complex, in particular for the tropospheric and total columns.

The Tropospheric Monitoring Instrument (TROPOMI), aboard the Sentinel-5 Precursor (S5P) satellite, launched on 13 October 2017, provides measurements of atmospheric trace gases and of cloud and aerosol properties at an unprecedented spatial resolution of approximately 7×3.5 km² (approx. 5.5×3.5 km² as of 6 August 2019), achieving near-global coverage in 1 d. The retrieval of nitrogen dioxide (NO₂) concentrations is a three-step procedure: slant column density (SCD) retrieval, separation of the SCD in its stratospheric and tropospheric components, and conversion of these into vertical column densities. This study focusses on the TROPOMI NO₂ SCD retrieval: the retrieval method used, the stability of the SCDs and the SCD uncertainties, and a comparison with the Ozone Monitoring Instrument (OMI) NO₂ SCDs. The statistical uncertainty, based on the spatial variability of the SCDs over a remote Pacific Ocean sector, is 8.63 µmol m⁻² for all pixels (9.45 µmol m⁻² for clear-sky pixels), which is very stable over time and some 30 % less than the long-term average over OMI–QA4ECV data (since the pixel size reduction TROPOMI uncertainties are ∼8 % larger). The SCD uncertainty reported by the differential optical absorption spectroscopy (DOAS) fit is about 10 % larger than the statistical uncertainty, while for OMI–QA4ECV the DOAS uncertainty is some 20 % larger than its statistical uncertainty. Comparison of the SCDs themselves over the Pacific Ocean, averaged over 1 month, shows that TROPOMI is about 5 % higher than OMI–QA4ECV, which seems to be due mainly to the use of the so-called intensity offset correction in OMI–QA4ECV but not in TROPOMI: turning that correction off means about 5 % higher SCDs. The row-to-row variation in the SCDs of TROPOMI, the “stripe amplitude”, is 2.15 µmol m⁻², while for OMI–QA4ECV it is a factor of ∼2 (∼5) larger in 2005 (2018); still, a so-called stripe correction of this non-physical across-track variation is useful for TROPOMI data. In short, TROPOMI shows a superior performance compared with OMI–QA4ECV and operates as anticipated from instrument specifications. The TROPOMI data used in this study cover 30 April 2018 up to 31 January 2020.

TROPOspheric Monitoring Instrument (TROPOMI), on‐board the Sentinel‐5 Precurser satellite, is a nadir‐viewing spectrometer measuring reflected sunlight in the ultraviolet, visible, near‐infrared, and shortwave infrared. From these spectra several important air quality and climate‐related atmospheric constituents are retrieved, including nitrogen dioxide (NO₂) at unprecedented spatial resolution from a satellite platform. We present the first retrievals of TROPOMI NO₂ over the Canadian Oil Sands, contrasting them with observations from the Ozone Monitoring Instrument satellite instrument, and demonstrate TROPOMI's ability to resolve individual plumes and highlight its potential for deriving emissions from individual mining facilities. Further, the first TROPOMI NO₂ validation is presented, consisting of aircraft and surface in situ NO₂ observations, and ground‐based remote‐sensing measurements between March and May 2018. Our comparisons show that the TROPOMI NO₂ vertical column densities are highly correlated with the aircraft and surface in situ NO₂ observations, and the ground‐based remote‐sensing measurements with a low bias (15–30 %); this bias can be reduced by improved air mass factors.

Global observations of tropospheric nitrogen dioxide (NO₂) columns have been shown to be feasible from space, but consistent multi-sensor records do not yet exist, nor are they covered by planned activities at the international level. Harmonised, multi-decadal records of NO₂ columns and their associated uncertainties can provide crucial information on how the emissions and concentrations of nitrogen oxides evolve over time. Here we describe the development of a new, community best-practice NO₂ retrieval algorithm based on a synthesis of existing approaches. Detailed comparisons of these approaches led us to implement an enhanced spectral fitting method for NO₂, a 1° × 1° TM5-MP data assimilation scheme to estimate the stratospheric background and improve air mass factor calculations. Guided by the needs expressed by data users, producers, and WMO GCOS guidelines, we incorporated detailed per-pixel uncertainty information in the data product, along with easily traceable information on the relevant quality aspects of the retrieval. We applied the improved QA4ECV NO₂ algorithm to the most current level-1 data sets to produce a complete 22-year data record that includes GOME (1995–2003), SCIAMACHY (2002–2012), GOME-2(A) (2007 onwards) and OMI (2004 onwards). The QA4ECV NO₂ spectral fitting recommendations and TM5-MP stratospheric column and air mass factor approach are currently also applied to S5P-TROPOMI. The uncertainties in the QA4ECV tropospheric NO₂ columns amount to typically 40 % over polluted scenes. The first validation results of the QA4ECV OMI NO₂ columns and their uncertainties over Tai'an, China, in June 2006 suggest a small bias (−2 %) and better precision than suggested by uncertainty propagation. We conclude that our improved QA4ECV NO₂ long-term data record is providing valuable information to quantitatively constrain emissions, deposition, and trends in nitrogen oxides on a global scale.

On board the Copernicus Sentinel-5 Precursor (S5P) platform, the TROPOspheric Monitoring Instrument (TROPOMI) is a double-channel, nadir-viewing grating spectrometer measuring solar back-scattered earthshine radiances in the ultraviolet, visible, near-infrared, and shortwave infrared with global daily coverage. In the ultraviolet range, its spectral resolution and radiometric performance are equivalent to those of its predecessor OMI, but its horizontal resolution at true nadir is improved by an order of magnitude. This paper introduces the formaldehyde (HCHO) tropospheric vertical column retrieval algorithm implemented in the S5P operational processor and comprehensively describes its various retrieval steps. Furthermore, algorithmic improvements developed in the framework of the EU FP7-project QA4ECV are described for future updates of the processor. Detailed error estimates are discussed in the light of Copernicus user requirements and needs for validation are highlighted. Finally, verification results based on the application of the algorithm to OMI measurements are presented, demonstrating the performances expected for TROPOMI.

Nitrogen dioxide (NO₂) is a regulated air pollutant that is of particular concern in many cities, where concentrations are high. Emissions of nitrogen oxides to the atmosphere lead to the formation of ozone and particulate matter, with adverse impacts on human health and ecosystems. The effects of emissions are often assessed through modeling based on inventories relying on indirect information that is often outdated or incomplete. Here we show that NO₂ measurements from the new, high-resolution TROPOMI satellite sensor can directly determine the strength and distribution of emissions from Paris. From the observed build-up of NO₂ pollution, we find highest emissions on cold weekdays in February 2018, and lowest emissions on warm weekend days in spring 2018. The new measurements provide information on the spatio-temporal distribution of emissions within a large city, and suggest that Paris emissions in 2018 are only 5–15% below inventory estimates for 2011–2012, reflecting the difficulty of meeting NO_x emission reduction targets.