Surface ozone data from the Chinese Ministry of Ecology and Environment (MEE) network show sustained increases across the country over the 2013–2019 period. Despite Phase 2 of the Clean Air Action Plan targeting ozone pollution, ozone was higher in 2018–2019 than in previous years. The mean summer 2013–2019 trend in maximum 8 h average (MDA8) ozone was 1.9 ppb a⁻¹ (p<0.01) across China and 3.3 ppb a⁻¹ (p<0.01) over the North China Plain (NCP). Fitting ozone to meteorological variables with a multiple linear regression model shows that meteorology played a significant but not dominant role in the 2013–2019 ozone trend, contributing 0.70 ppb a⁻¹ (p<0.01) across China and 1.4 ppb a⁻¹ (p=0.02) over the NCP. Rising June–July temperatures over the NCP were the main meteorological driver, particularly in recent years (2017–2019), and were associated with increased foehn winds. NCP data for 2017–2019 show a 15 % decrease in fine particulate matter (PM_2.5) that may be driving the continued anthropogenic increase in ozone, as well as unmitigated emissions of volatile organic compounds (VOCs). VOC emission reductions, as targeted by Phase 2 of the Chinese Clean Air Action Plan, are needed to reverse the increase in ozone.

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.

Determining effective strategies for mitigating surface ozone (O₃) pollution requires knowledge of the relative ambient concentrations of its precursors, NO_x, and VOCs. The space‐based tropospheric column ratio of formaldehyde to NO₂ (FNR) has been used as an indicator to identify NO_x‐limited versus NO_x‐saturated O₃ formation regimes. Quantitative use of this indicator ratio is subject to three major uncertainties: (1) the split between NO_x‐limited and NO_x‐saturated conditions may shift in space and time, (2) the ratio of the vertically integrated column may not represent the near‐surface environment, and (3) satellite products contain errors. We use the GEOS‐Chem global chemical transport model to evaluate the quantitative utility of FNR observed from the Ozone Monitoring Instrument over three northern midlatitude source regions. We find that FNR in the model surface layer is a robust predictor of the simulated near‐surface O₃ production regime. Extending this surface‐based predictor to a column‐based FNR requires accounting for differences in the HCHO and NO₂ vertical profiles. We compare four combinations of two OMI HCHO and NO₂ retrievals with modeled FNR. The spatial and temporal correlations between the modeled and satellite‐derived FNR vary with the choice of NO₂ product, while the mean offset depends on the choice of HCHO product. Space‐based FNR indicates that the spring transition to NO_x‐limited regimes has shifted at least a month earlier over major cities (e.g., New York, London, and Seoul) between 2005 and 2015. This increase in NO_x sensitivity implies that NO_x emission controls will improve O₃ air quality more now than it would have a decade ago.

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.

The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S-5P) platform will measure ultraviolet earthshine radiances at high spectral and improved spatial resolution (pixel size of 7 km × 3.5 km at nadir) compared to its predecessors OMI and GOME-2. This paper presents the sulfur dioxide (SO₂) vertical column retrieval algorithm implemented in the S-5P operational processor UPAS (Universal Processor for UV/VIS Atmospheric Spectrometers) and comprehensively describes its various retrieval steps. The spectral fitting is performed using the differential optical absorption spectroscopy (DOAS) method including multiple fitting windows to cope with the large range of atmospheric SO₂ columns encountered. It is followed by a slant column background correction scheme to reduce possible biases or across-track-dependent artifacts in the data. The SO₂ vertical columns are obtained by applying air mass factors (AMFs) calculated for a set of representative a priori profiles and accounting for various parameters influencing the retrieval sensitivity to SO₂. Finally, the algorithm includes an error analysis module which is fully described here. We also discuss verification results (as part of the algorithm development) and future validation needs of the TROPOMI SO₂ algorithm.

This work presents global tropospheric formaldehyde columns retrieved from near-UV radiance measurements performed by the GOME instrument onboard ERS-2 since 1995, and by SCIAMACHY, in operation on ENVISAT since the end of 2002. A special effort has been made to ensure the coherence and quality of the CH₂O dataset covering the period 1996–2007. Optimised DOAS settings are proposed in order to reduce the impact of two important sources of error in the derivation of slant columns, namely, the polarisation anomaly affecting the SCIAMACHY spectra around 350 nm, and a major absorption band of the O₄ collision complex centred near 360 nm. The air mass factors are determined from scattering weights generated using radiative transfer calculations taking into account the cloud fraction, the cloud height and the ground albedo. Vertical profile shapes of CH₂O are provided by the global CTM IMAGES based on an up-to-date representation of emissions, atmospheric transport and photochemistry. A comprehensive error analysis is presented. This includes errors on the slant columns retrieval and errors on the air mass factors which are mainly due to uncertainties in the a priori profile and in the cloud properties. The major features of the retrieved formaldehyde column distribution are discussed and compared with previous CH₂O datasets over the major emission regions.