In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97^∘ N, 4.93^∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO₂), the oxygen collision complex (O₄) and ozone (O₃) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO₂ in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

We present a new product with explicit aerosol corrections, POMINO-TROPOMI, for tropospheric nitrogen dioxide (NO₂) vertical column densities (VCDs) over East Asia, based on the newly launched TROPOspheric Monitoring Instrument with an unprecedented high horizontal resolution. Compared to the official TM5-MP-DOMINO (OFFLINE) product, POMINO-TROPOMI shows stronger concentration gradients near emission source locations and better agrees with MAX-DOAS measurements (R²=0.75; NMB=0.8 % versus R²=0.68, $\mathrm{NMB}=-\mathrm{41.9}$ %). Sensitivity tests suggest that implicit aerosol corrections, as in TM5-MP-DOMINO, lead to underestimations of NO₂ columns by about 25 % over the polluted northern East China region. Reducing the horizontal resolution of a priori NO₂ profiles would underestimate the retrieved NO₂ columns over isolated city clusters in western China by 35 % but with overestimates of more than 50 % over many offshore coastal areas. The effect of a priori NO₂ profiles is more important under calm conditions.

We present the inter-comparison of delta slant column densities (SCDs) and vertical profiles of nitrous acid (HONO) derived from measurements of different multi-axis differential optical absorption spectroscopy (MAX-DOAS) instruments and using different inversion algorithms during the Second Cabauw Inter-comparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) in September 2016 at Cabauw, the Netherlands (51.97^∘ N, 4.93^∘ E). The HONO vertical profiles, vertical column densities (VCDs), and near-surface volume mixing ratios are compared between different MAX-DOAS instruments and profile inversion algorithms for the first time. Systematic and random discrepancies of the HONO results are derived from the comparisons of all data sets against their median values. Systematic discrepancies of HONO delta SCDs are observed in the range of $\pm \mathrm{0.3}\times {\mathrm{10}}^{\mathrm{15}}$ molec. cm⁻², which is half of the typical random discrepancy of 0.6×10¹⁵ molec. cm⁻². For a typical high HONO delta SCD of 2×10¹⁵ molec. cm⁻², the relative systematic and random discrepancies are about 15 % and 30 %, respectively. The inter-comparison of HONO profiles shows that both systematic and random discrepancies of HONO VCDs and near-surface volume mixing ratios (VMRs) are mostly in the range of $\sim \pm \mathrm{0.5}\times {\mathrm{10}}^{\mathrm{14}}$ molec. cm⁻² and $\sim \pm \mathrm{0.1}$ ppb (typically ∼20 %). Further we find that the discrepancies of the retrieved HONO profiles are dominated by discrepancies of the HONO delta SCDs. The profile retrievals only contribute to the discrepancies of the HONO profiles by ∼5 %. However, some data sets with substantially larger discrepancies than the typical values indicate that inappropriate implementations of profile inversion algorithms and configurations of radiative transfer models in the profile retrievals can also be an important uncertainty source. In addition, estimations of measurement uncertainties of HONO dSCDs, which can significantly impact profile retrievals using the optimal estimation method, need to consider not only DOAS fit errors, but also atmospheric variability, especially for an instrument with a DOAS fit error lower than $\sim \mathrm{3}\times {\mathrm{10}}^{\mathrm{14}}$ molec. cm⁻². The MAX-DOAS results during the CINDI-2 campaign indicate that the peak HONO levels (e.g. near-surface VMRs of ∼0.4 ppb) often appeared in the early morning and below 0.2 km. The near-surface VMRs retrieved from the MAX-DOAS observations are compared with those measured using a co-located long-path DOAS instrument. The systematic differences are smaller than 0.15 and 0.07 ppb during early morning and around noon, respectively. Since true HONO values at high altitudes are not known in the absence of real measurements, in order to evaluate the abilities of profile inversion algorithms to respond to different HONO profile shapes, we performed sensitivity studies using synthetic HONO delta SCDs simulated by a radiative transfer model with assumed HONO profiles. The tests indicate that the profile inversion algorithms based on the optimal estimation method with proper configurations can reproduce the different HONO profile shapes well. Therefore we conclude that the features of HONO accumulated near the surface derived from MAX-DOAS measurements are expected to represent the ambient HONO profiles well.

Tropospheric vertical column densities (VCDs) of nitrogen dioxide (NO₂) retrieved from sun-synchronous satellite instruments have provided abundant NO₂ data for environmental studies, but such data are limited by retrieval uncertainties and insufficient temporal sampling (e.g., once a day). The Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020 monitors NO₂ at an unprecedented hourly resolution during the daytime. Here we present a research product for tropospheric NO₂ VCDs, referred to as POMINO–GEMS (where POMINO is the Peking University OMI NO₂ algorithm). We develop a hybrid retrieval method combining GEMS, TROPOMI (TROPOspheric Monitoring Instrument) and GEOS-CF (Global Earth Observing System Composition Forecast) data to generate hourly tropospheric NO₂ slant column densities (SCDs). We then derive tropospheric NO₂ air mass factors (AMFs) with explicit corrections for surface reflectance anisotropy and aerosol optical effects through parallelized pixel-by-pixel radiative transfer calculations. Prerequisite cloud parameters are retrieved with the O₂–O₂ algorithm by using ancillary parameters consistent with those used in NO₂ AMF calculations. The initial retrieval of POMINO–GEMS tropospheric NO₂ VCDs for June–August 2021 exhibits strong hotspot signals over megacities and distinctive diurnal variations over polluted and clean areas. POMINO–GEMS NO₂ VCDs agree with the POMINO–TROPOMI v1.2.2 product (R=0.98; NMB = 4.9 %) over East Asia, with slight differences associated with satellite viewing geometries and cloud and aerosol properties affecting the NO₂ retrieval. POMINO–GEMS also shows good agreement with the following: OMNO2 (Ozone Monitoring Instrument (OMI) NO₂ Standard Product) v4 (R=0.87; NMB = −16.8 %); and GOME-2 (Global Ozone Monitoring Experiment-2) GDP (GOME Data Processor) 4.8 (R=0.83; NMB = −1.5 %) NO₂ products. POMINO–GEMS shows small biases against ground-based MAX-DOAS (multi-axis differential optical absorption spectroscopy) NO₂ VCD data at nine sites (NMB = −11.1 %), with modest or high correlation in diurnal variation at six urban and suburban sites (R from 0.60 to 0.96). The spatiotemporal variation in POMINO–GEMS correlates well with mobile car MAX-DOAS measurements in the Three Rivers source region on the Tibetan Plateau (R=0.81). Surface NO₂ concentrations estimated from POMINO–GEMS VCDs are consistent with measurements from the Ministry of Ecology and Environment of China for spatiotemporal variation (R=0.78; NMB = −26.3 %) and diurnal variation at all, urban, suburban and rural sites (R≥0.96). POMINO–GEMS data will be made freely available for users to study the spatiotemporal variations, sources and impacts of NO₂.