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.

Multi-axis differential optical absorption spectroscopy (MAX-DOAS) and direct sun NO₂ vertical column network data are used to investigate the accuracy of tropospheric NO₂ column measurements of the GOME-2 instrument on the MetOp-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO₂ field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO₂ column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −34 % for GOME-2A and −24 % for OMI. These biases are further reduced to −24 % and −18 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI are also performed, showing less scatter but also a slightly larger median tropospheric NO₂ column bias with respect to the ensemble of MAX-DOAS and direct sun measurements.

The second Cabauw Intercomparison of Nitrogen Dioxide measuring Instruments (CINDI-2) took place in Cabauw (the Netherlands) in September 2016 with the aim of assessing the consistency of multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of tropospheric species (NO₂, HCHO, O₃, HONO, CHOCHO and O₄). This was achieved through the coordinated operation of 36 spectrometers operated by 24 groups from all over the world, together with a wide range of supporting reference observations (in situ analysers, balloon sondes, lidars, long-path DOAS, direct-sun DOAS, Sun photometer and meteorological instruments). In the presented study, the retrieved CINDI-2 MAX-DOAS trace gas (NO₂, HCHO) and aerosol vertical profiles of 15 participating groups using different inversion algorithms are compared and validated against the colocated supporting observations, with the focus on aerosol optical thicknesses (AOTs), trace gas vertical column densities (VCDs) and trace gas surface concentrations. The algorithms are based on three different techniques: six use the optimal estimation method, two use a parameterized approach and one algorithm relies on simplified radiative transport assumptions and analytical calculations. To assess the agreement among the inversion algorithms independent of inconsistencies in the trace gas slant column density acquisition, participants applied their inversion to a common set of slant columns. Further, important settings like the retrieval grid, profiles of O₃, temperature and pressure as well as aerosol optical properties and a priori assumptions (for optimal estimation algorithms) have been prescribed to reduce possible sources of discrepancies. The profiling results were found to be in good qualitative agreement: most participants obtained the same features in the retrieved vertical trace gas and aerosol distributions; however, these are sometimes at different altitudes and of different magnitudes. Under clear-sky conditions, the root-mean-square differences (RMSDs) among the results of individual participants are in the range of 0.01–0.1 for AOTs, (1.5–15) $\times {\mathrm{10}}^{\mathrm{14}}\mathrm{molec}.{\mathrm{cm}}^{-\mathrm{2}}$ for trace gas (NO₂, HCHO) VCDs and (0.3–$\mathrm{8})\times {\mathrm{10}}^{\mathrm{10}}\mathrm{molec}.{\mathrm{cm}}^{-\mathrm{3}}$ for trace gas surface concentrations. These values compare to approximate average optical thicknesses of 0.3, trace gas vertical columns of $\mathrm{90}\times {\mathrm{10}}^{\mathrm{14}}\mathrm{molec}.{\mathrm{cm}}^{-\mathrm{2}}$ and trace gas surface concentrations of $\mathrm{11}\times {\mathrm{10}}^{\mathrm{10}}\mathrm{molec}.{\mathrm{cm}}^{-\mathrm{3}}$ observed over the campaign period. The discrepancies originate from differences in the applied techniques, the exact implementation of the algorithms and the user-defined settings that were not prescribed. For the comparison against supporting observations, the RMSDs increase to a range of 0.02–0.2 against AOTs from the Sun photometer, (11–$\mathrm{55})\times {\mathrm{10}}^{\mathrm{14}}\mathrm{molec}.{\mathrm{cm}}^{-\mathrm{2}}$ against trace gas VCDs from direct-sun DOAS observations and (0.8–$\mathrm{9})\times {\mathrm{10}}^{\mathrm{10}}\mathrm{molec}.{\mathrm{cm}}^{-\mathrm{3}}$ against surface concentrations from the long-path DOAS instrument. This increase in RMSDs is most likely caused by uncertainties in the supporting data, spatiotemporal mismatch among the observations and simplified assumptions particularly on aerosol optical properties made for the MAX-DOAS retrieval. As a side investigation, the comparison was repeated with the participants retrieving profiles from their own differential slant column densities (dSCDs) acquired during the campaign. In this case, the consistency among the participants degrades by about 30 % for AOTs, by 180 % (40 %) for HCHO (NO₂) VCDs and by 90 % (20 %) for HCHO (NO₂) surface concentrations. In former publications and also during this comparison study, it was found that MAX-DOAS vertically integrated aerosol extinction coefficient profiles systematically underestimate the AOT observed by the Sun photometer. For the first time, it is quantitatively shown that for optimal estimation algorithms this can be largely explained and compensated by considering biases arising from the reduced sensitivity of MAX-DOAS observations to higher altitudes and associated a priori assumptions.

Inter-annual variability and long-term trends in tropospheric ozone are both environmental and climate concerns. Ozone measured at Mt Waliguan Observatory (WLG, 3816 m a.s.l.) on the Tibetan Plateau over the period of 1994–2013 has increased significantly by 0.2–0.3 ppbv yr⁻¹ during spring and autumn but shows a much smaller trend in winter and no significant trend in summer. Here we explore the factors driving the observed ozone changes at WLG using backward trajectory analysis, chemistry–climate model hindcast simulations (GFDL AM3), a trajectory-mapped ozonesonde data set, and several climate indices. A stratospheric ozone tracer implemented in GFDL AM3 indicates that stratosphere-to-troposphere transport (STT) can explain ∼ 60 % of the simulated springtime ozone increase at WLG, consistent with an increase in the NW air-mass frequency inferred from the trajectory analysis. Enhanced STT associated with the strengthening of the mid-latitude jet stream contributes to the observed high ozone anomalies at WLG during the springs of 1999 and 2012. During autumn, observations at WLG are more heavily influenced by polluted air masses originating from South East Asia than in the other seasons. Rising Asian anthropogenic emissions of ozone precursors are the key driver of increasing autumnal ozone observed at WLG, as supported by the GFDL AM3 model with time-varying emissions, which captures the observed ozone increase (0.26 ± 0.11 ppbv yr⁻¹). AM3 simulates a greater ozone increase of 0.38 ± 0.11 ppbv yr⁻¹ at WLG in autumn under conditions with strong transport from South East Asia and shows no significant ozone trend in autumn when anthropogenic emissions are held constant in time. During summer, WLG is mostly influenced by easterly air masses, but these trajectories do not extend to the polluted regions of eastern China and have decreased significantly over the last 2 decades, which likely explains why summertime ozone measured at WLG shows no significant trend despite ozone increases in eastern China. Analysis of the Trajectory-mapped Ozonesonde data set for the Stratosphere and Troposphere (TOST) and trajectory residence time reveals increases in direct ozone transport from the eastern sector during autumn, which adds to the autumnal ozone increase. We further examine the links of ozone variability at WLG to the quasi-biennial oscillation (QBO), the East Asian summer monsoon (EASM), and the sunspot cycle. Our results suggest that the 2–3-, 3–7-, and 11-year periodicities are linked to the QBO, EASM index, and sunspot cycle, respectively. A multivariate regression analysis is performed to quantify the relative contributions of various factors to surface ozone concentrations at WLG. Through an observational and modelling analysis, this study demonstrates the complex relationships between surface ozone at remote locations and its dynamical and chemical influencing factors.

Enhanced aerosol abundance in the upper troposphere and lower stratosphere (UTLS) associated with the Asian summer monsoon (ASM) is referred to as the Asian Tropopause Aerosol Layer (ATAL). The chemical composition, microphysical properties, and climate effects of aerosols in the ATAL have been the subject of discussion over the past decade. In this work, we use the ECHAM/MESSy Atmospheric Chemistry (EMAC) general circulation model at a relatively fine grid resolution (about 1.1×1.1 ^∘) to numerically simulate the emissions, chemistry, and transport of aerosols and their precursors in the UTLS within the ASM anticyclone during the years 2010–2012. We find a pronounced maximum of aerosol extinction in the UTLS over the Tibetan Plateau, which to a large extent is caused by mineral dust emitted from the northern Tibetan Plateau and slope areas, lofted to an altitude of at least 10 km, and accumulating within the anticyclonic circulation. We also find that the emissions and convection of ammonia in the central main body of the Tibetan Plateau make a great contribution to the enhancement of gas-phase NH₃ in the UTLS over the Tibetan Plateau and ASM anticyclone region. Our simulations show that mineral dust, water-soluble compounds, such as nitrate and sulfate, and associated liquid water dominate aerosol extinction in the UTLS within the ASM anticyclone. Due to shielding of high background sulfate concentrations outside the anticyclone from volcanoes, a relative minimum of aerosol extinction within the anticyclone in the lower stratosphere is simulated, being most pronounced in 2011, when the Nabro eruption occurred. In contrast to mineral dust and nitrate concentrations, sulfate increases with increasing altitude due to the larger volcano effects in the lower stratosphere compared to the upper troposphere. Our study indicates that the UTLS over the Tibetan Plateau can act as a well-defined conduit for natural and anthropogenic gases and aerosols into the stratosphere.

In this study the consistency between MAX-DOAS measurements and radiative transfer simulations of the atmospheric O₄ absorption is investigated on 2 mainly cloud-free days during the MAD-CAT campaign in Mainz, Germany, in summer 2013. In recent years several studies indicated that measurements and radiative transfer simulations of the atmospheric O₄ absorption can only be brought into agreement if a so-called scaling factor (<1) is applied to the measured O₄ absorption. However, many studies, including those based on direct sunlight measurements, came to the opposite conclusion, that there is no need for a scaling factor. Up to now, there is no broad consensus for an explanation of the observed discrepancies between measurements and simulations. Previous studies inferred the need for a scaling factor from the comparison of the aerosol optical depths derived from MAX-DOAS O₄ measurements with that derived from coincident sun photometer measurements. In this study a different approach is chosen: the measured O₄ absorption at 360 nm is directly compared to the O₄ absorption obtained from radiative transfer simulations. The atmospheric conditions used as input for the radiative transfer simulations were taken from independent data sets, in particular from sun photometer and ceilometer measurements at the measurement site. This study has three main goals: first all relevant error sources of the spectral analysis, the radiative transfer simulations and the extraction of the input parameters used for the radiative transfer simulations are quantified. One important result obtained from the analysis of synthetic spectra is that the O₄ absorptions derived from the spectral analysis agree within 1 % with the corresponding radiative transfer simulations at 360 nm. Based on the results from sensitivity studies, recommendations for optimised settings for the spectral analysis and radiative transfer simulations are given. Second, the measured and simulated results are compared for 2 selected cloud-free days with similar aerosol optical depths but very different aerosol properties. On 18 June, measurements and simulations agree within their (rather large) uncertainties (the ratio of simulated and measured O₄ absorptions is found to be 1.01±0.16). In contrast, on 8 July measurements and simulations significantly disagree: for the middle period of that day the ratio of simulated and measured O₄ absorptions is found to be 0.82±0.10, which differs significantly from unity. Thus, for that day a scaling factor is needed to bring measurements and simulations into agreement. Third, recommendations for further intercomparison exercises are derived. One important recommendation for future studies is that aerosol profile data should be measured at the same wavelengths as the MAX-DOAS measurements. Also, the altitude range without profile information close to the ground should be minimised and detailed information on the aerosol optical and/or microphysical properties should be collected and used. The results for both days are inconsistent, and no explanation for a O₄ scaling factor could be derived in this study. Thus, similar but more extended future studies should be performed, including more measurement days and more instruments. Also, additional wavelengths should be included.