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This paper reports on ground-based validation of the atmospheric OClO data record produced within the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC SAF) using the Global Ozone Monitoring Experiment (GOME)-2A and GOME-2B instrument measurements, covering the 2007–2016 and 2013–2016 periods, respectively. OClO slant column densities are compared to correlative measurements collected from nine Zenith-Scattered-Light Differential Optical Absorption Spectroscopy (ZSL-DOAS) instruments from the Network for the Detection of Atmospheric Composition Change (NDACC) distributed in both the Arctic and Antarctic. Sensitivity tests are performed on the ground-based data to estimate the impact of the different OClO DOAS analysis settings. On this basis, we infer systematic uncertainties of about 25 % (i.e., about 3.75×1013 molec. cm−2) between the different ground-based data analyses, reaching total uncertainties ranging from about 26 % to 33 % for the different stations (i.e., around 4 to 5×1013 molec. cm−2). Time series at the different sites show good agreement between satellite and ground-based data for both the inter-annual variability and the overall OClO seasonal behavior. GOME-2A results are found to be noisier than those of GOME-2B, especially after 2011, probably due to instrumental degradation effects. Daily linear regression analysis for OClO-activated periods yield correlation coefficients of 0.8 for GOME-2A and 0.87 for GOME-2B, with slopes with respect to the ground-based data ensemble of 0.64 and 0.72, respectively. Satellite minus ground-based offsets are within 8×1013 molec. cm−2, with some differences between GOME-2A and GOME-2B depending on the station. Overall, considering all the stations, a median offset of about -2.2×1013 molec. cm−2 is found for both GOME-2 instruments.

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.

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.

International audience; Multi-axis differential optical absorption spec-troscopy (MAX-DOAS) tropospheric NO 2 column retrievals from four European measurement stations are compared to simulations from five regional air quality models which contribute to the European regional ensemble forecasts and re-analyses of the operational Copernicus Atmosphere Monitoring Service (CAMS). Compared to other observational data usually applied for regional model evaluation, MAX-DOAS data are closer to the regional model data in terms of horizontal and vertical resolution, and multiple measurements are available during daylight, so that, for example, diurnal cycles of trace gases can be investigated. In general, there is good agreement between simulated and retrieved NO 2 column values for individual MAX-DOAS measurements with correlations between 35 % and 70 % for individual models and 45 % to 75 % for the ensemble median for tropospheric NO 2 vertical column densities (VCDs), indicating that emissions, transport and tropospheric chemistry of NO x are on average well simulated. However, large differences are found for individual pollution plumes observed by MAX-DOAS. Most of the models overestimate seasonal cycles for the majority of MAX-DOAS sites investigated. At the urban stations, weekly cycles are reproduced well, but the decrease towards the weekend is underestimated and diurnal cycles are overall not well represented. In particular , simulated morning rush hour peaks are not confirmed by MAX-DOAS retrievals, and models fail to reproduce observed changes in diurnal cycles for weekdays versus weekends. The results of this study show that future model development needs to concentrate on improving representation of diurnal cycles and associated temporal scalings.

73 pags. 49 figs., 41 tabs.-- Open Access funded by Creative Commons Atribution Licence 4.0, In this study the consistency between MAX-DOAS measurements and radiative transfer simulations of the atmospheric O 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 O absorption can only be brought into agreement if a so-called scaling factor (, We are thankful for several external data sets which were used in this study: temperature and pressure profiles from the ERA-Interim reanalysis data set were provided by the European Centre for Medium-Range Weather Forecasts. In situ measurements of trace gas and aerosol concentrations, as well as meteorological data, were performed by the environmental monitoring services of the states of Rhineland-Palatinate and Hesse (http://www.luft-rlp.de, last access: 29 April 2019 and https://www.hlnug.de/themen/luft/luftmessnetz.html, last access: 29 April 2019).

‘Candidatus Liberibacter asiaticus’, the bacterium associated with citrus Huanglongbing (HLB), was reported from Uganda and tentatively from Tanzania, posing a threat to citriculture in Africa. Two surveys of citrus expressing typical HLB symptoms were conducted in Uganda, Kenya, and Tanzania to verify reports of ‘Ca. L. asiaticus’ and to assess the overall threat of HLB to eastern and southern African citrus production. Samples were analyzed for the presence of ‘Candidatus Liberibacter’ species by real-time PCR and partial sequencing of three housekeeping genes, 16S rDNA, rplJ, and omp. ‘Ca. L. africanus’, the bacterium historically associated with HLB symptoms in Africa, was detected in several samples. However, samples positive in real-time PCR for ‘Ca. L. asiaticus’ were shown not to contain ‘Ca. L. asiaticus’ by sequencing. Sequences obtained from these samples were analogous to ‘Ca. L. africanus subsp. clausenae’, identified from an indigenous Rutaceae species in South Africa, and not to ‘Ca. L. asiaticus’. Results indicate a nontarget amplification of the real-time assay and suggest that previous reports of ‘Ca. L. asiaticus’ from Uganda and Tanzania may be mis-identifications of ‘Ca. L. africanus subsp. clausenae’. This subspecies was additionally detected in individual Diaphorina citri and Trioza erytreae specimens recovered from collection sites. This is the first report of ‘Ca. L. africanus subsp. clausenae’ infecting citrus and being associated with HLB symptoms in this host.

Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of nitrous acid (HONO) and its precursor NO2 (nitrogen dioxide) as well as aerosols have been performed daily in Beijing city centre (39.98° N, 116.38° E) from July 2008 to April 2009 and at the suburban site of Xianghe (39.75° N, 116.96° E) located ~60 km east of Beijing from March 2010 to December 2012. This extensive dataset allowed for the first time the investigation of the seasonal cycle of HONO as well as its diurnal variation in and in the vicinity of a megacity. Our study was focused on the HONO and NO2 near-surface concentrations (0–200 m layer) and total vertical column densities (VCDs) and also aerosol optical depths (AODs) and extinction coefficients retrieved by applying the Optimal Estimation Method to the MAX-DOAS observations. Monthly averaged HONO near-surface concentrations at local noon display a strong seasonal cycle with a maximum in late fall/winter (~0.8 and 0.7 ppb at Beijing and Xianghe, respectively) and a minimum in summer (~0.1 ppb at Beijing and 0.03 ppb at Xianghe). The seasonal cycles of HONO and NO2 appear to be highly correlated, with correlation coefficients in the 0.7–0.9 and 0.5–0.8 ranges at Beijing and Xianghe, respectively. The stronger correlation of HONO with NO2 and also with aerosols observed in Beijing suggests possibly larger role of NO2 conversion into HONO in the Beijing city center than at Xianghe. The observed diurnal cycle of HONO near-surface concentration shows a maximum in the early morning (about 1 ppb at both sites) likely resulting from night-time accumulation, followed by a decrease to values of about 0.1–0.4 ppb around local noon. The HONO / NO2 ratio shows a similar pattern with a maximum in the early morning (values up to 0.08) and a decrease to ~0.01–0.02 around local noon. The seasonal and diurnal cycles of the HONO near-surface concentration are found to be similar in shape and in relative amplitude to the corresponding cycles of the HONO total VCD and are therefore likely driven mainly by the balance between HONO sources and the photolytic sink, whereas dilution effects appear to play only a minor role. The estimation of OH radical production from HONO and O3 photolysis based on retrieved HONO near-surface concentrations and calculated photolysis rates indicate that in the 0–200 m altitude range, HONO is by far the largest source of OH radicals in winter as well as in the early morning at all seasons, while the contribution of O3 dominates in summer from mid-morning until mid-afternoon.

International audience; Several initiatives are ongoing to improve the traceability of atmospheric composition measurements to agreed standards, to quantify and reduce the measurement uncertainties, and to quantify and improve the mutual consistency of atmospheric data across ground-based networks and between satellite missions (e.g., WMO O3S-DQA, SI2N, ESA CCI and FRM projects, EU FP7 QA4ECV and EU H2020 GAIA-CLIM). With increasing data accuracy, natural variability has become a non-negligible source of error for single measurements, for their comparison, for their merging and for their assimilation in chemistry-transport models. Therefore a corresponding effort has been undertaken to quantify the specific uncertainties resulting from spatial inhomogeneities and temporal variability in the atmospheric field. Quantifying such uncertainties is for instance a key objective of the current EU H2020 project GAIA-CLIM.In this contribution, we present a detailed quantification of the impact of natural inhomogeneities and vari- ability on several corner-stone ozone observing systems and on the intercomparison of their data (both for validation and for merging purposes). This study is based on OSSEs (Observing System Simulation Experiments) of existing ozone observing systems carried out with the OSSSMOSE simulator, which includes explicit descrip- tion of multi-dimensional effects impacting the remote sensing of atmospheric ozone (Verhoelst et al., AMT, 2015). Simulations are presented for total ozone column and ozone profile measurements acquired by GAW- contributing reference networks (Brewer, Dobson, NDACC DOAS, GAW/NDACC/SHADOZ ozonesondes) and by nadir-viewing UV-visible satellites (GOME, SCIAMACHY, GOME-2, Sentinel-5p TROPOMI). Illustrations show how natural inhomogeneities and variability introduces additional uncertainties: on the representativeness of single measurements, on comparisons between different (imperfectly) co-located measurements, and on higher-level products based on an averaging of unevenly distributed data.As a generalization of these case-by-case results, we describe on the global scale how those additional un- certainties depend on measurement type, latitude, season, atmospheric phenomena etc., as this determines the fitness-for-purpose of the current ozone observing systems and provides valuable feedback for the de- sign/optimization of ground networks and satellite missions.

The trend in stratospheric NO2 column at the NDACC (Network for the Detection of Atmospheric Composition Change) station of Jungfraujoch (46.5° N, 8.0° E) is assessed using ground-based FTIR and zenith-scattered visible sunlight SAOZ measurements over the period 1990 to 2009 as well as a composite satellite nadir data set constructed from ERS-2/GOME, ENVISAT/SCIAMACHY, and METOP-A/GOME-2 observations over the 1996–2009 period. To calculate the trends, a linear least squares regression model including explanatory variables for a linear trend, the mean annual cycle, the quasi-biennial oscillation (QBO), solar activity, and stratospheric aerosol loading is used. For the 1990–2009 period, statistically indistinguishable trends of −3.7 ± 1.1% decade−1 and −3.6 ± 0.9% decade−1 are derived for the SAOZ and FTIR NO2 column time series, respectively. SAOZ, FTIR, and satellite nadir data sets show a similar decrease over the 1996–2009 period, with trends of −2.4 ± 1.1% decade−1, −4.3 ± 1.4% decade−1, and −3.6 ± 2.2% decade−1, respectively. The fact that these declines are opposite in sign to the globally observed +2.5% decade−1 trend in N2O, suggests that factors other than N2O are driving the evolution of stratospheric NO2 at northern mid-latitudes. Possible causes of the decrease in stratospheric NO2 columns have been investigated. The most likely cause is a change in the NO2/NO partitioning in favor of NO, due to a possible stratospheric cooling and a decrease in stratospheric chlorine content, the latter being further confirmed by the negative trend in the ClONO2 column derived from FTIR observations at Jungfraujoch. Decreasing ClO concentrations slows the NO + ClO → NO2 + Cl reaction and a stratospheric cooling slows the NO + O3 → NO2 + O2 reaction, leaving more NOx in the form of NO. The slightly positive trends in ozone estimated from ground- and satellite-based data sets are also consistent with the decrease of NO2 through the NO2 + O3 → NO3 + O2 reaction. Finally, we cannot rule out the possibility that a strengthening of the Dobson-Brewer circulation, which reduces the time available for N2O photolysis in the stratosphere, could also contribute to the observed decline in stratospheric NO2 above Jungfraujoch.

No Abstract.

Comparisons between satellite and ground-based measurements of the atmosphere are inevitably affected by natural variability due to mismatches in spatial and temporal co-location. These additional terms in the comparison error budget are quantified here for total ozone column comparisons using an Observing System Simulation Experiment. Even when using tight co-location criteria, atmospheric variability is found to impact the comparisons significantly. Part of this work was funded by the Belgian Science Policy O ce (BELSPO) and ESA via the ProDEx projects A3C and ACROSAT, and by the EU H2020 project GAIA-CLIM (Ares(2014)3708963/Project 640276). Finally, the 20 authors acknowledge the pioneering research carried out in 2008–2012 by C. De Clercq and S. Vandenbussche and funded by the EU FP6 project GEOmon (FP6-2005-Global-4-036677) and ProDEx project SECPEA.

This document is the final report of the Intercalibration of ground-based spectrometers and Lidars - Extension 2012-2013. It summarizes the activities performed in the period from November 2012 until December 2013 and the main results obtained.

The catalysis with complex (I) proceeds mostly chemoselectively for a wide range of linear or cyclic, aromatic or aliphatic ketones.

International audience; Among the main objectives of the Network for Detection of Atmospheric Composition Changes (NDACC) are the validation and eventually the correction of biases between long-term series of data provided by various satellite instruments. This presentation deals with the evaluation of satellite total ozone retrievals using observations performed by the NDACC/SAOZ UV-Vis spectrometers at all latitudes since 1988. Recently, the full series of SAOZ total ozone measurements in the visible Chappuis bands has been revised according to the spectral analysis and Air Mass Factor (AMF) settings recommended by the NDACC UV-Vis Working Group (Hendrick et al., 2011). The comparison involves overpass observations from the TOMS, GOME-GDP4, SCIAMACHY-TOSOMI, SCIAMACHY-OL3, OMI-TOMS, OMI-DOAS and METOP-GOME-2 satellite instruments. Significant improvement is obtained after applying the new O3 AMFs, although systematic seasonal differences between SAOZ and all other instruments still remain. These are shown to originate from (i) stratospheric temperature and solar zenith angle (SZA) dependences in the satellites retrievals, (ii) longitudinal modulations and seasonal variations of tropospheric ozone columns not accounted for in the ozone profile climatology used for calculating the AMFs, and (iii) uncertainties on the climatological stratospheric ozone profiles in polar winter conditions. For those measurements mostly sensitive to stratospheric temperature like TOMS, OMI-TOMS or to SZA like SCIAMACHY-TOSOMI, the application of temperature and SZA corrections results in the almost complete removal of the seasonal difference with SAOZ, improving significantly the consistency between satellite and ground-based total ozone series. However, small but sometimes signi cant biases still remain after applying those corrections. A similar exercise is in progress with SAOZ NO2 data sets, using AMFs calculated from a profile climatology based on HALOE, SAGE II, POAM III and SAOZ balloon profiles. The consistency with GOME/ERS2, SCIAMACHY/ENVISAT and OMI/AURA NO2 total columns is currently examined. In this presentation, we will focus on the resulting evaluation of ozone and NO2 total columns biases, temperature and SZA dependences of the various satellite instruments.

Tropospheric BrO was measured by a ground-based remote-sensing spectrometer at Halley in Antarctica, and BrO was measured by remote-sensing spectrometers in space using similar spectral regions and Differential Optical Absorption Spectroscopy 5 (DOAS) analyses. Near-surface BrO was simultaneously measured at Halley by Chemical Ionisation Mass Spectrometry (CIMS), and in an earlier year near-surface BrO was measured at Halley over a long path by a DOAS spectrometer. During enhancement episodes, total amounts of tropospheric BrO from the ground-based remotesensor were similar to those from space, but if we assume that the BrO was confined 10 to the boundary layer they were very much larger than values measured by either near-surface technique. This large apparent discrepancy can be resolved if substantial amounts of BrO were in the free troposphere during most enhancement episodes. Amounts observed by the ground-based remote sensor at different elevation angles, and their formal inversions to vertical profiles, also show that much of the BrO was of15 ten in the free troposphere. This is consistent with the � 5 day lifetime of Bry, from the enhanced BrO observed during some Antarctic blizzards, and from aircraft measurements of BrO well above the surface in the Arctic.

The Optical Spectrograph and Infra-Red Imager System (OSIRIS) and the Atmospheric Chemistry Experiment (ACE) have been taking measurements from space since 2001 and 2003, respectively. This paper presents intercomparisons between ozone and NO2 measured by the ACE and OSIRIS satellite instruments and by ground-based instruments at the Polar Environment Atmospheric Research Laboratory (PEARL), which is located at Eureka, Canada (80° N, 86° W) and is operated by the Canadian Network for the Detection of Atmospheric Change (CANDAC). The ground-based instruments included in this study are four zenith-sky differential optical absorption spectroscopy (DOAS) instruments, one Bruker Fourier transform infrared spectrometer (FTIR) and four Brewer spectrophotometers. Ozone total columns measured by the DOAS instruments were retrieved using new Network for the Detection of Atmospheric Composition Change (NDACC) guidelines and agree to within 3.2%. The DOAS ozone columns agree with the Brewer spectrophotometers with mean relative differences that are smaller than 1.5%. This suggests that for these instruments the new NDACC data guidelines were successful in producing a homogenous and accurate ozone dataset at 80° N. Satellite 14-52 km ozone and 17-40 km NO2 partial columns within 500 km of PEARL were calculated for ACE-FTS Version 2.2 (v2.2) plus updates, ACE-FTS v3.0, ACE-MAESTRO (Measurements of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation) v1.2 and OSIRIS SaskMART v5.0x ozone and Optimal Estimation v3.0 NO2 data products. The new ACE-FTS v3.0 and the validated ACE-FTS v2.2 partial columns are nearly identical, with mean relative differences of 0.0 ± 0.2% for ozone and -0.2 ± 0.1% for v2.2 minus v3.3 NO2. Ozone columns were constructed from 14-52 km satellite and 0-14 km ozonesonde partial columns and compared with the ground-based total column measurements. The satellite-plus-sonde measurements agree with the ground-based ozone total columns with mean relative differences of 0.1-7.3%. For NO2, partial columns from 17 km upward were scaled to noon using a photochemical model. Mean relative differences between OSIRIS, ACE-FTS and ground-based NO2 measurements do not exceed 20%. ACE-MAESTRO measures more NO2 than the other instruments, with mean relative differences of 25-52%. Seasonal variation in the differences between partial columns is observed, suggesting that there are systematic errors in the measurements, the photochemical model corrections, and/or in the coincidence criteria. For ozone spring-time measurements, additional coincidence criteria based on stratospheric temperature and the location of the polar vortex were found to improve agreement between some of the instruments. For ACE-FTS v2.2 minus Bruker FTIR, the 2007-2009 spring-time mean relative difference improved from -5.0 ± 0.4% to -3.1 ± 0.8% with the dynamical selection criteria. This was the largest improvement, likely because both instruments measure direct sunlight and therefore have well-characterized lines-of-sight compared with scattered sunlight measurements. For NO2, the addition of a ±1° latitude coincidence criterion improved spring-time intercomparison results, likely due to the sharp latitudinal gradient of NO2 during polar sunrise. The differences between satellite and ground-based measurements do not show any obvious trends over the missions, indicating that both the ACE and OSIRIS instruments continue to perform well.

Póster presentado en: Quadrennial Ozone Symposium 2012 celebrado del 27 al 31 de agosto de 2012 en Toronto, Canadá This work has been partially funded by NORS, UE FP7 Project under grant agreement n° 284421 and AMISOC, CGL2011‐24891, from the Spanish Plan for Research, Development and Innovation.