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In this study we focus on the retrieval of aerosol and trace gas vertical profiles from multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations for the first time over Thessaloniki, Greece. We use two independent inversion algorithms for the profile retrievals: the Mexican MAX-DOAS Fit (MMF) and the Mainz Profile Algorithm (MAPA). The former is based on the optimal estimation method (OEM), while the latter follows a parameterization approach. We evaluate the performance of MMF and MAPA, and we validate their retrieved products with ancillary data measured by other co-located reference instruments. The trace gas differential slant column densities (dSCDs), simulated by the forward models, are in good agreement, except for HCHO, where larger scatter is observed due to the increased spectral noise of the measurements in the UV. We find an excellent agreement between the tropospheric column densities of NO2 retrieved by MMF and MAPA (slope=1.009, Pearson's correlation coefficient R=0.982) and a good correlation for the case of HCHO (R=0.927). For aerosols, we find better agreement for the aerosol optical depths (AODs) in the visible (i.e., at 477 nm) compared to the UV (at 360 nm), and we show that the agreement strongly depends on the O4 scaling factor that is used in the analysis. The agreement for NO2 and HCHO near-surface concentrations is similar to the comparison of the integrated columns with slightly decreased correlation coefficients. The seasonal mean vertical profiles that are retrieved by MMF and MAPA are intercompared, and the seasonal variation in all species along with possible sources is discussed. The AODs retrieved by the MAX-DOAS are validated by comparing them with AOD values measured by a CIMEL sun photometer and a Brewer spectrophotometer. Four different flagging schemes were applied to the data in order to evaluate their performance. Qualitatively, a generally good agreement is observed for both wavelengths, but we find a systematic bias from the CIMEL sun photometer and Brewer spectrophotometer measurements, due to the limited sensitivity of the MAX-DOAS in retrieving information at higher altitudes, especially in the UV. An in-depth validation of the aerosol vertical profiles retrieved by the MAX-DOAS is not possible since only in very few cases is the true aerosol profile known during the period of study. However, we examine four cases, where the MAX-DOAS provided a generally good estimation of the shape of the profiles retrieved by a co-located multi-wavelength lidar system. The NO2 near-surface concentrations are validated against in situ observations, and the comparison of both MMF and MAPA revealed good agreement with correlation coefficients of R=0.78 and R=0.73, respectively. Finally, the effect of the O4 scaling factor is investigated by intercomparing the integrated columns retrieved by the two algorithms and also by comparing the AODs derived by MAPA for different values of the scaling factor with AODs measured by the CIMEL sun photometer and the Brewer spectrophotometer.

We present a formalism that relates the vertical column density (VCD) of the oxygen collision complex O2–O2 (denoted as O4 below) to surface (2 m) values of temperature and pressure, based on physical laws. In addition, we propose an empirical modification which also accounts for surface relative humidity (RH). This allows for simple and quick calculation of the O4 VCD without the need for constructing full vertical profiles. The parameterization reproduces the true O4 VCD, as derived from vertically integrated profiles, within -0.7±1.2% (mean ± SD) for Weather Research and Forecasting (WRF) simulations around Germany, 0.2±1.8 % for global reanalysis data (ERA5), and -0.3±1.4% for Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) radiosonde measurements around the world. When applied to measured surface values, uncertainties of 1 K, 1 hPa, and 16 % for temperature, pressure, and RH correspond to relative uncertainties of the O4 VCD of 0.3 %, 0.2 %, and 1 %, respectively. The proposed parameterization thus provides a simple and accurate formula for the calculation of the O4 VCD which is expected to be useful in particular for MAX-DOAS applications.

Since its first confirmed case in December 2019, coronavirus disease 2019 (COVID-19) has become a worldwide pandemic with more than 90 million confirmed cases by January 2021. Countries around the world have enforced lockdown measures to prevent the spread of the virus, introducing a temporal change of air pollutants such as nitrogen dioxide (NO2) that are strongly related to transportation, industry, and energy. In this study, NO2 variations over regions with strong responses to COVID-19 are analysed using datasets from the Global Ozone Monitoring Experiment-2 (GOME-2) sensor aboard the EUMETSAT Metop satellites and TROPOspheric Monitoring Instrument (TROPOMI) aboard the EU/ESA Sentinel-5 Precursor satellite. The global GOME-2 and TROPOMI NO2 datasets are generated at the German Aerospace Center (DLR) using harmonized retrieval algorithms; potential influences of the long-term trend and seasonal cycle, as well as the short-term meteorological variation, are taken into account statistically. We present the application of the GOME-2 data to analyze the lockdown-related NO2 variations for morning conditions. Consistent NO2 variations are observed for the GOME-2 measurements and the early afternoon TROPOMI data: regions with strong social responses to COVID-19 in Asia, Europe, North America, and South America show strong NO2 reductions of $\sim $ ∼ 30–50% on average due to restriction of social and economic activities, followed by a gradual rebound with lifted restriction measures.

14 pags., 10 figs., Iodine plays a vital role in oxidation chemistry over Antarctica, with past observations showing highly elevated levels of iodine oxide (IO) leading to severe depletion of boundary layer ozone in West Antarctica. Here, we present MAX-DOAS-based (multi-axis differential absorption spectroscopy) observations of IO over three summers (2015-2017) at the Indian Antarctic bases of Bharati and Maitri. IO was observed during all the campaigns with mixing ratios below 2ĝ€¯pptv (parts per trillion by volume) for the three summers, which are lower than the peak levels observed in West Antarctica. This suggests that sources in West Antarctica are different or stronger than sources of iodine compounds in East Antarctica, the nature of which is still uncertain. Vertical profiles estimated using a profile retrieval algorithm showed decreasing gradients with a peak in the lower boundary layer. The ground-based instrument retrieved vertical column densities (VCDs) were approximately a factor of 3 to 5 higher than the VCDs reported using satellite-based instruments, which is most likely related to the sensitivities of the measurement techniques. Air mass back-trajectory analysis failed to highlight a source region, with most of the air masses coming from coastal or continental regions. This study highlights the variation in iodine chemistry in different regions in Antarctica and the importance of a long-term dataset to validate models estimating the impacts of iodine chemistry., The ISEA campaigns are organized by the National Centre for Polar and Ocean Research (NCPOR), Ministry of Earth Sciences (MOES), Government of India.IITM and NCPOR are funded by MOES, Government of India.

We investigate effects of the three-dimensional (3D) structure of volcanic plumes on the retrieval results of satellite and ground-based UV–Vis observations. For the analysis of such measurements, 1D scenarios are usually assumed (the atmospheric properties only depend on altitude). While 1D assumptions are well suited for the analysis of many atmospheric phenomena, they are usually less appropriate for narrow trace gas plumes. For UV–Vis satellite instruments with large ground pixel sizes like the Global Ozone Monitoring Experiment-2 (GOME-2), the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) or the Ozone Monitoring Instrument (OMI), 3D effects are of minor importance, but usually these observations are not sensitive to small volcanic plumes. In contrast, observations of the TROPOspheric Monitoring Instrument (TROPOMI) on board Sentinel-5P have a much smaller ground pixel size (3.5 × 5.5 km2). Thus, on the one hand, TROPOMI can detect much smaller plumes than previous instruments. On the other hand, 3D effects become more important, because the TROPOMI ground pixel size is smaller than the height of the troposphere and also smaller than horizontal atmospheric photon path lengths in the UV–Vis spectral range. In this study we investigate the following 3D effects using Monte Carlo radiative transfer simulations: (1) the light-mixing effect caused by horizontal photon paths, (2) the saturation effect for strong SO2 absorption, (3) geometric effects related to slant illumination and viewing angles and (4) plume side-effects related to slant illumination angles and photons reaching the sensor from the sides of volcanic plumes. The first two effects especially can lead to a strong and systematic underestimation of the true trace gas content if 1D retrievals are applied (more than 50 % for the light-mixing effect and up to 100 % for the saturation effect). Besides the atmospheric radiative transfer, the saturation effect also affects the spectral retrievals. Geometric effects have a weaker influence on the quantitative analyses but can lead to a spatial smearing of elevated plumes or even to virtual double plumes. Plume side-effects are small for short wavelengths but can become large for longer wavelengths (up to 100 % for slant viewing and illumination angles). For ground-based observations, most of the above-mentioned 3D effects are not important because of the narrow field of view (FOV) and the closer distance between the instrument and the volcanic plume. However, the light-mixing effect shows a similar strong dependence on the horizontal plume extension as for satellite observations and should be taken into account for the analysis of ground-based observations.

We present high spatial resolution (up to 2.2×2.2 km2) simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n) (MESSy-fied ECHAM and COSMO models nested n times). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMRs) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly-resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS (Multiple AXis Differential Optical Absorption Spectroscopy) measurements performed at Mainz (49.99∘ N, 8.23∘ E) were used to evaluate the simulated tropospheric vertical column densities (VCDs) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles (≤8∘), small biases in the range of −14 % to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases, indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly-resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when vertical mixing is suppressed, and the atmospheric lifetime of NO2 is relatively long.

In this study we compare measured and simulated O4 absorptions for conditions of extremely low aerosol optical depth (between 0.034 to 0.056 at 360 nm) on one day during a ship cruise in the tropical Atlantic. For such conditions, the uncertainties related to imperfect knowledge of aerosol properties don't significantly affect the comparison results. We find that the simulations underestimate the measurements by 15 % to 20 %. Even for simulations without any aerosols the measured O4 absorptions are still systematically higher than the simulation results. The observed discrepancies can not be explained by uncertainties of the measurements and simulations and thus indicate a fundamental inconsistency between simulations and measurements.

We used a global long-term (1995–2015) data set of total column water vapour (TCWV) derived from satellite observations to quantify to which extent the temporal patterns of various teleconnections can be identified in this data set. To our knowledge, such a comprehensive global TCWV data set was rarely used for teleconnection studies. One important property of the TCWV data set is that it is purely based on observational data. We developed a new empirical method to decide whether a teleconnection index is significantly detected in the global data set. We compared our new method to well-established hypothesis tests and found good agreement with the results of our approach. Based on our empirical method more than 40 teleconnection indices were significantly detected in the global TCWV data set derived from satellite observations. In addition to the satellite data we also applied our method to other global data sets derived from ERA-Interim. One important finding is that the spatial patterns obtained for the ERA TCWV data are very similar to the observational TCWV data set indicating a high consistency between the satellite and ERA data. Moreover, similar results are also found for two selections of ERA data (either all data or mainly clear-sky data). This finding indicates that the clear-sky bias of the satellite data set is negligible for the results of this study. However, for some indices, also systematic differences in the spatial patterns between the satellite and model data set were found probably indicating possible shortcomings in the model data. For most “traditional” teleconnection data sets (surface temperature, surface pressure, geopotential heights and meridional winds at different altitudes) a smaller number of significant teleconnection indices was found than for the TCWV data sets, while for zonal winds at different altitudes, the number of significant teleconnection indices (up to > 50) was higher. The strongest teleconnection signals were found in the data sets of tropospheric geopotential heights and surface pressure. In all global data sets, no “other indices” (solar variability, stratospheric AOD or hurricane frequency) were significantly detected. Since many teleconnection indices are strongly correlated, we also applied our method to a set of orthogonalised indices, which represent the dominant independent temporal teleconnection patterns. The number of significantly detected orthogonalised indices (20) was found to be much smaller than for the original indices (42). Based on the orthogonalised indices we derived the global spatial distribution of the cumulative effect of teleconnections. The strongest effect on the TCWV is found in the tropics and high latitudes.

We present comprehensive long-term ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of aerosols, nitrogen dioxide (NO2), and formaldehyde (HCHO) from Mohali (30.667∘ N, 76.739∘ E; ∼310 m above mean sea level), located in the densely populated Indo-Gangetic Plain (IGP) of India. We investigate the temporal variation in tropospheric columns, surface volume mixing ratio (VMR), and vertical profiles of aerosols, NO2, and HCHO and identify factors driving their ambient levels and distributions for the period from January 2013 to June 2017. We observed mean aerosol optical depth (AOD) at 360 nm, tropospheric NO2 vertical column density (VCD), and tropospheric HCHO VCD for the measurement period to be 0.63 ± 0.51, (6.7 ± 4.1) × 1015, and (12.1 ± 7.5) × 1015 molecules cm−2, respectively. Concerning the tropospheric NO2 VCDs, Mohali was found to be less polluted than urban and suburban locations of China and western countries, but comparable HCHO VCDs were observed. For the more than 4 years of measurements during which the region around the measurement location underwent significant urban development, we did not observe obvious annual trends in AOD, NO2, and HCHO. High tropospheric NO2 VCDs were observed in periods with enhanced biomass and biofuel combustion (e.g. agricultural residue burning and domestic burning for heating). Highest tropospheric HCHO VCDs were observed in agricultural residue burning periods with favourable meteorological conditions for photochemical formation, which in previous studies have shown an implication for high ambient ozone also over the IGP. Highest AOD is observed in the monsoon season, indicating possible hygroscopic growth of the aerosol particles. Most of the NO2 is located close to the surface, whereas significant HCHO is present at higher altitudes up to 600 m during summer indicating active photochemistry at high altitudes. The vertical distribution of aerosol, NO2, and HCHO follows the change in boundary layer height (BLH), from the ERA5 dataset of European Centre for Medium-Range Weather Forecasts, between summer and winter. However, deep convection during the monsoon transports the pollutants at high altitudes similar to summer despite a shallow ERA5 BLH. Strong gradients in the vertical profiles of HCHO are observed during the months when primary anthropogenic sources dominate the formaldehyde production. High-resolution MODIS AOD measurements correlate well but were systematically higher than MAX-DOAS AODs. The ground-based MAX-DOAS measurements were used to evaluate three NO2 data products and two HCHO data products of the Ozone Monitoring Instrument (OMI) for the first time over India and the IGP. NO2 VCDs from OMI correlate reasonably with MAX-DOAS VCDs but are lower by ∼30 %–50 % due to the difference in vertical sensitivities and the rather large OMI footprint. OMI HCHO VCDs exceed the MAX-DOAS VCDs by up to 30 %. We show that there is significant scope for improvement in the a priori vertical profiles of trace gases, which are used in OMI retrievals. The difference in vertical representativeness was found to be crucial for the observed biases in NO2 and HCHO surface VMR intercomparisons. Using the ratio of NO2 and HCHO VCDs measured from MAX-DOAS, we have found that the peak daytime ozone production regime is sensitive to both NOx and VOCs in winter but strongly sensitive to NOx in other seasons.

The QA4ECV (Quality Assurance for Essential Climate Variables) version 1.1 stratospheric and tropospheric NO2 vertical column density (VCD) climate data records (CDRs) from the OMI (Ozone Monitoring Instrument) satellite sensor are validated using NDACC (Network for the Detection of Atmospheric Composition Change) zenith-scattered light differential optical absorption spectroscopy (ZSL-DOAS) and multi-axis DOAS (MAX-DOAS) data as a reference. The QA4ECV OMI stratospheric VCDs have a small bias of ∼0.2 Pmolec.cm-2 (5 %–10 %) and a dispersion of 0.2 to 1 Pmolec.cm-2 with respect to the ZSL-DOAS measurements. QA4ECV tropospheric VCD observations from OMI are restricted to near-cloud-free scenes, leading to a negative sampling bias (with respect to the unrestricted scene ensemble) of a few peta molecules per square centimetre (Pmolec.cm-2) up to −10 Pmolec.cm-2 (−40 %) in one extreme high-pollution case. The QA4ECV OMI tropospheric VCD has a negative bias with respect to the MAX-DOAS data (−1 to −4 Pmolec.cm-2), which is a feature also found for the OMI OMNO2 standard data product. The tropospheric VCD discrepancies between satellite measurements and ground-based data greatly exceed the combined measurement uncertainties. Depending on the site, part of the discrepancy can be attributed to a combination of comparison errors (notably horizontal smoothing difference error), measurement/retrieval errors related to clouds and aerosols, and the difference in vertical smoothing and a priori profile assumptions.

Atmospheric water plays a key role for the Earth’s energy budget and temperature distribution via radiative effects (clouds and vapour) and latent heat transport. Thus, the distribution and transport of water vapour are closely linked to atmospheric dynamics on different spatiotemporal scales. In this context, global monitoring of the water vapour distribution is essential for numerical weather prediction, climate modelling, and a better understanding of climate feedbacks.Total column water vapour (TCWV), or integrated water vapour, can be retrieved from satellite spectra in the visible “blue” spectral range (430-450nm) using Differential Optical Absorption Spectroscopy (DOAS). The UV-vis spectral range offers several advantages for monitoring the global water vapour distribution: for instance, it allows for accurate, straightforward and consistent retrievals over ocean and land surface even under partly-cloudy conditions.To investigate changes in the TCWV distribution from space, the Ozone Monitoring Instrument (OMI) on board NASA’s Aura satellite is particularly promising as it provides long-term measurements (late 2004-ongoing) with daily global coverage.Here, we present a global analysis of trends of total column water vapour retrieved from multiple years of OMI observations (2005-2021) and put our results in context to TCWV trends from other climate data records (e.g. reanalysis models or satellite measurements). Additionally, we investigate if the assumption of constant relative humidity over climatological time periods is fulfilled.Furthermore, we demonstrate that it is possible to infer changes in the global atmospheric circulation directly from the global TCWV distribution: More precisely, we show that trends in changes in the location of the Hadley cell as well as its poleward expansion can be determined from the latitudinal TCWV distribution using a simple, straightforward and robust methodology.

We present a method to infer CO2 emissions from individual power plants based on satellite observations of co-emitted nitrogen dioxide (NO2), which could serve as complementary verification of bottom-up inventories or be used to supplement these inventories. We demonstrate its utility on eight large and isolated US power plants, where accurate stack emission estimates of both gases are available for comparison. In the first step of our methodology, we infer nitrogen oxides (NOx) emissions from US power plants using Ozone Monitoring Instrument (OMI) NO2 tropospheric vertical column densities (VCDs) averaged over the ozone season (May–September) and a “top-down” approach that we previously developed. Second, we determine the relationship between NOx and CO2 emissions based on the direct stack emissions measurements reported by continuous emissions monitoring system (CEMS) programs, accounting for coal quality, boiler firing technology, NOx emission control device type, and any change in operating conditions. Third, we estimate CO2 emissions for power plants using the OMI-estimated NOx emissions and the CEMS NOx∕CO2 emission ratio. We find that the CO2 emissions estimated by our satellite-based method during 2005–2017 are in reasonable agreement with the US CEMS measurements, with a relative difference of 8 %±41 % (mean ± standard deviation). The broader implication of our methodology is that it has the potential to provide an additional constraint on CO2 emissions from power plants in regions of the world without reliable emissions accounting. We explore the feasibility by comparing the derived NOx∕CO2 emission ratios for the US with those from a bottom-up emission inventory for other countries and applying our methodology to a power plant in South Africa, where the satellite-based emission estimates show reasonable consistency with other independent estimates. Though our analysis is limited to a few power plants, we expect to be able to apply our method to more US (and world) power plants when multi-year data records become available from new OMI-like sensors with improved capabilities, such as the TROPOspheric Monitoring Instrument (TROPOMI), and upcoming geostationary satellites, such as the Tropospheric Emissions: Monitoring Pollution (TEMPO) instrument.

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 (

The Mainz profile algorithm (MAPA) derives vertical profiles of aerosol extinction and trace gas concentrations from MAX-DOAS measurements of slant column densities under multiple elevation angles. This paper presents (a) a detailed description of the MAPA (v0.98), (b) results for the CINDI-2 campaign, and (c) sensitivity studies on the impact of a priori assumptions such as flag thresholds. Like previous profile retrieval schemes developed at MPIC, MAPA is based on a profile parameterization combining box profiles, which also might be lifted, and exponential profiles. But in contrast to previous inversion schemes based on least-square fits, MAPA follows a Monte Carlo approach for deriving those profile parameters yielding best match to the MAX-DOAS observations. This is much faster and directly provides physically meaningful distributions of profile parameters. In addition, MAPA includes an elaborated flagging scheme for the identification of questionable or dubious results. The AODs derived with MAPA for the CINDI-2 campaign show good agreement with AERONET if a scaling factor of 0.8 is applied for O4, and the respective NO2 and HCHO surface mixing ratios match those derived from coincident long-path DOAS measurements. MAPA results are robust with respect to modifications of the a priori MAPA settings within plausible limits.

In urban areas, road traffic is a dominant source of nitrogen oxides (NOx=NO+NO2). Although the emissions from individual vehicles are regulated by the European emission standards, real driving emissions often exceed these limits. In this study, two multi-axis differential optical absorption spectroscopy (MAX-DOAS) instruments on opposite sides of the motorway were used to measure the NO2 absorption caused by road traffic at the A60 motorway close to Mainz, Germany. In combination with wind data, the total NOx emissions for the occurring traffic volume can be estimated. Hereto, the ozone-dependent photochemical equilibrium between NO and NO2 is considered. We show that for 10 May 2019 the measured emissions exceed the maximum expected emissions calculated from the European emission standards for standardised test cycles by a factor of 11±7. One major advantage of the method used here is that MAX-DOAS measurements are very sensitive to the integrated NO2 concentration close to the surface. Thus, all emitted NO2 molecules are detected independently from their altitude, and therefore the whole emission plume originating from the nearby motorway is captured, which is a key advantage compared to other approaches such as in situ measurements.

Nitrogen oxides ( NO x ≡ NO + NO 2 ) in the upper troposphere (UT) have a large impact on global tropospheric ozone and OH (the main atmospheric oxidant). New cloud-sliced observations of UT NO2 at 450–280 hPa ( ∼6 –9 km) from the Ozone Monitoring Instrument (OMI) produced by NASA and the Royal Netherlands Meteorological Institute (KNMI) provide global coverage to test our understanding of the factors controlling UT NOx . We find that these products offer useful information when averaged over coarse scales ( 20 ∘ × 32 ∘ , seasonal), and that the NASA product is more consistent with aircraft observations of UT NO2 . Correlation with Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) satellite observations of lightning flash frequencies suggests that lightning is the dominant source of NOx to the upper troposphere except for extratropical latitudes in winter. The NO2 background in the absence of lightning is 10–20 pptv. We infer a global mean NOx yield of 280±80 moles per lightning flash, with no significant difference between the tropics and midlatitudes, and a global lightning NOx source of 5.9±1.7 Tg N a −1 . There is indication that the NOx yield per flash increases with lightning flash footprint and with flash energy.

On board of 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.

Air mass factor (AMF) calculation is the largest source of uncertainty in NO2 and HCHO satellite retrievals in situations with enhanced trace gas concentrations in the lower troposphere. Structural uncertainty arises when different retrieval methodologies are applied within the scientific community to the same satellite observations. Here, we address the issue of AMF structural uncertainty via a detailed comparison of AMF calculation methods that are structurally different between seven retrieval groups for measurements from the Ozone Monitoring Instrument (OMI). We estimate the escalation of structural uncertainty in every sub-step of the AMF calculation process. This goes beyond the algorithm uncertainty estimates provided in state-of-the-art retrievals, which address the theoretical propagation of uncertainties for one particular retrieval algorithm only. We find that top-of-atmosphere reflectances simulated by four radiative transfer models (RTMs) (DAK, McArtim, SCIATRAN and VLIDORT) agree within 1.5 %. We find that different retrieval groups agree well in the calculations of altitude resolved AMFs from different RTMs (to within 3 %), and in the tropospheric AMFs (to within 6 %) as long as identical ancillary data (surface albedo, terrain height, cloud parameters and trace gas profile) and cloud and aerosol correction procedures are being used. Structural uncertainty increases sharply when retrieval groups use their preference for ancillary data, cloud and aerosol correction. On average, we estimate the AMF structural uncertainty to be 42 % over polluted regions and 31 % over unpolluted regions, mostly driven by substantial differences in the a priori trace gas profiles, surface albedo and cloud parameters. Sensitivity studies for one particular algorithm indicate that different cloud correction approaches result in substantial AMF differences in polluted conditions (5 to 40 % depending on cloud fraction and cloud pressure, and 11 % on average) even for low cloud fractions (

Power plant exhausts can be identified and quantified from satellite observations., Satellite observations of nitrogen dioxide (NO2) provide valuable information on the location and strength of NOx emissions, but spatial resolution is limited by horizontal transport and smearing of temporal averages due to changing wind fields. In this study, we map NOx emissions on high spatial resolution from TROPOMI observations of NO2 combined with wind fields based on the continuity equation. The divergence of horizontal fluxes proves to be highly sensitive for point sources like exhaust stacks. Thus, NOx emissions from individual power plants can be resolved and quantified even on top of considerably high urban pollution from the Saudi Arabian capital city Riyadh. This allows us to catalog NOx emissions from large point sources globally, as demonstrated for South Africa and Germany, with a detection limit of about 0.11 kg/s down to 0.03 kg/s for ideal conditions.

North China (NC), namely Huabei in Chinese, is one of the most severely polluted regions in China, and the air pollution issues in this region have received a worldwide attention. We performed ground-based Multi Axis Differential Absorption Spectroscopy (MAX-DOAS) measurements at Gucheng, (39°08′N, 115°40′E), a rural site of North China about 110 km southwest of Beijing, from September 2008 to September 2010. The tropospheric vertical column densities (VCDs) of NO2 and SO2 were retrieved using the so-called geometric approximation. The results show that the tropospheric NO2 and SO2 VCDs over NC have nearly the same seasonal variation pattern, with the maximum in winter and minimum in summer, while their diurnal variations are different. We also compared the tropospheric NO2 and SO2 VCDs from our MAX-DOAS measurements with several products of corresponding OMI (Ozone Monitoring Instrument) satellite observations. While in summer good agreement is found, the satellite observations systematically underestimate the tropospheric NO2 in winter over the polluted rural area of NC, probably mostly due to the so called aerosol shielding effect. In contrast, for SO2 no such clear conclusion can be drawn, probably owing to the larger uncertainties from MAX-DOAS and in particular satellite retrievals. This indicates that improvements of the retrieval algorithm for MAX-DOAS and off-line corrections of satellite measurements for the tropospheric SO2 VCDs should be given more emphasis in the future.

Multi-axis differential optical absorption spectroscopy (MAX-DOAS) is a widely used measurement technique for the detection of a variety of atmospheric trace gases. Using inverse modelling, the observation of trace gas column densities along different lines of sight enables the retrieval of aerosol and trace gas vertical profiles in the atmospheric boundary layer using appropriate retrieval algorithms. In this study, the ability of eight profile retrieval algorithms to reconstruct vertical profiles is assessed on the basis of synthetic measurements. Five of the algorithms are based on the optimal estimation method, two on parametrised approaches, and one using an analytical approach without involving any radiative transfer modelling. The synthetic measurements consist of the median of simulated slant column densities of O4 at 360 and 477 nm, as well as of HCHO at 343 nm and NO2 at 477 nm, from seven datasets simulated by five different radiative transfer models. Simulations are performed for a combination of 10 trace gas and 11 aerosol profiles, as well as 11 elevation angles, three solar zenith, and three relative azimuth angles. Overall, the results from the different algorithms show moderate to good performance for the retrieval of vertical profiles, surface concentrations, and total columns. Except for some outliers, the root-mean-square difference between the true and retrieved state ranges between (0.05–0.1) km−1 for aerosol extinction and (2.5–5.0) ×1010 molec cm−3 for HCHO and NO2 concentrations.

Ground‐based measurements of tropospheric ozone (O3) are valuable for studies of atmospheric chemistry, air pollution, climate change, and for satellite validation. The Multi Axis Differential Optical Absorption Spectroscopy (MAX‐DOAS) technique has been widely used to derive vertical profiles of trace gases and aerosols in the troposphere. However, tropospheric O3 has not yet been satisfactorily derived from MAX‐DOAS measurements due to the influence of stratospheric O3 absorption. In this study, we developed two new retrieval approaches for tropospheric O3 from MAX‐DOAS measurements. In method 1, stratospheric O3 profiles from external data sources are considered in the retrieval. In method 2, stratospheric and tropospheric O3 are separated based on the temperature‐dependent differences between tropospheric and stratospheric O3 absorption structures in the UV spectral range. The feasibility of both methods is first verified by applying them to synthetic spectra. Then they are applied to real MAX‐DOAS measurements recorded during the CINDI‐2 campaign in Cabauw, the Netherlands (September 2016). The obtained results are compared with independent O3 measurements and global chemical transport model simulations. Good agreement of the near‐surface O3 concentrations with the independent data sets is found for both methods. However, tropospheric O3 profiles are only reasonably derived using method 1, while they are significantly overestimated at altitudes above 1 km using method 2, probably due to the approximation of the ring spectra used to correct the rotational Raman scattering structures in the DOAS fit. Advantages and disadvantages of both methods are discussed and improvement directions are suggested for further studies.

Knowledge of the total column water vapour (TCWV) global distribution is fundamental for climate analysis and weather monitoring. In this work, we present the retrieval algorithm used to derive the operational TCWV from the GOME-2 sensors aboard EUMETSAT's MetOp-A and MetOp-B satellites and perform an extensive inter-comparison in order to evaluate their consistency and temporal stability. For the analysis, the GOME-2 data sets are generated by DLR in the framework of the EUMETSAT O3M-SAF project using the GOME Data Processor (GDP) version 4.7. The retrieval algorithm is based on a classical Differential Optical Absorption Spectroscopy (DOAS) method and combines a H2O and O2 retrieval for the computation of the trace gas vertical column density. We introduce a further enhancement in the quality of the H2O total column by optimizing the cloud screening and developing an empirical correction in order to eliminate the instrument scan angle dependencies. The overall consistency between measurements from the newer GOME-2 instrument on board of the MetOp-B platform and the GOME-2/MetOp-A data is evaluated in the overlap period (December 2012–June 2014). Furthermore, we compare GOME-2 results with independent TCWV data from the ECMWF ERA-Interim reanalysis, with SSMIS satellite measurements during the full period January 2007–June 2014 and against the combined SSM/I + MERIS satellite data set developed in the framework of the ESA DUE GlobVapour project (January 2007–December 2008). Global mean biases as small as ±0.035 g cm−2 are found between GOME-2A and all other data sets. The combined SSM/I-MERIS sample and the ECMWF ERA-Interim data set are typically drier than the GOME-2 retrievals, while on average GOME-2 data overestimate the SSMIS measurements by only 0.006 g cm−2. However, the size of these biases is seasonally dependent. Monthly average differences can be as large as 0.1 g cm−2, based on the analysis against SSMIS measurements, which include only data over ocean. The seasonal behaviour is not as evident when comparing GOME-2 TCWV to the ECMWF ERA-Interim and the SSM/I+MERIS data sets, since the different biases over land and ocean surfaces partly compensate each other. Studying two exemplary months, we estimate regional differences and identify a very good agreement between GOME-2 total columns and all three data sets, especially for land areas, although some discrepancies (bias larger than ±0.5 g cm−2) over ocean and over land areas with high humidity or a relatively large surface albedo are observed.

Water vapour plays a dominant role in the climate change debate. However, observing water vapour over a climatological time period in a consistent and homogeneous manner is challenging. On one hand, networks of ground-based instruments able to retrieve homogeneous integrated water vapour (IWV) data sets are being set up. Typical examples are Global Navigation Satellite System (GNSS) observation networks such as the International GNSS Service (IGS), with continuous GPS (Global Positioning System) observations spanning over the last 15+ years, and the AErosol RObotic NETwork (AERONET), providing long-term observations performed with standardized and well-calibrated sun photometers. On the other hand, satellite-based measurements of IWV already have a time span of over 10 years (e.g. AIRS) or are being merged to create long-term time series (e.g. GOME, SCIAMACHY, and GOME-2). This study performs an intercomparison of IWV measurements from satellite devices (in the visible, GOME/SCIAMACHY/GOME-2, and in the thermal infrared, AIRS), in situ measurements (radiosondes) and ground-based instruments (GPS, sun photometer), to assess their use in water vapour trends analysis. To this end, we selected 28 sites world-wide for which GPS observations can directly be compared with coincident satellite IWV observations, together with sun photometer and/or radiosonde measurements. The mean biases of the different techniques compared to the GPS estimates vary only between −0.3 to 0.5 mm of IWV. Nevertheless these small biases are accompanied by large standard deviations (SD), especially for the satellite instruments. In particular, we analysed the impact of clouds on the IWV agreement. The influence of specific issues for each instrument on the intercomparison is also investigated (e.g. the distance between the satellite ground pixel centre and the co-located ground-based station, the satellite scan angle, daytime/nighttime differences). Furthermore, we checked if the properties of the IWV scatter plots between these different instruments are dependent on the geography and/or altitude of the station. For all considered instruments, the only dependency clearly detected is with latitude: the SD of the IWV observations with respect to the GPS IWV retrievals decreases with increasing latitude and decreasing mean IWV.

Ground-based measurements of scattered sunlight by the Multi Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) have been carried out at an urban site (39.95° N, 116.32° E) in Beijing megacity since 6 August 2008. In this study, we retrieved the tropospheric NO2 vertical column densities (VCDs) over Beijing from these MAX-DOAS observations from August 2008 to September 2011. Over this period, the daytime (08:00–17:00 Beijing Time (BJT, which equals UTC + 8)) mean tropospheric NO2 VCDs varied from 0.5 to 13.3 with an average of 3.6 during summertime, and from 0.2 to 16.8 with an average of 5.8 during wintertime, all in units of 1016 molecules cm−2. The average diurnal variation patterns of tropospheric NO2 over Beijing appeared to be rather different from one season to another, indicating differences in the emission strength and atmospheric lifetime. In contrast to previous studies, we find a small weekly cycle of the tropospheric NO2 VCD over Beijing. The NO2 VCD in the late afternoon was the largest on Saturday and the lowest on Sunday, and in the morning it reached a clear maximum on Wednesday. We also find a post-Olympic Games effect, with 39–54% decrease in the tropospheric NO2 VCD over Beijing estimated for August of 2008, compared to the following years. The tropospheric NO2 VCDs derived by our ground MAX-DOAS measurements show a good correlation with SCIAMACHY and OMI satellite data. However, compared with the MAX-DOAS measurements, the satellite observations underestimate the tropospheric NO2 VCDs over Beijing systematically, by 43% for SCIAMACHY and 26–38% for OMI (DOMINO v2.0 and DOMINO v1.02). Based on radiative transfer simulations, we show that the aerosol shielding effect can explain this underestimation, while the gradient smoothing effect caused by the coarse spatial resolution of the satellite observations could play an additional role.

Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements were performed in a rural location of southwestern Ontario during the Border Air Quality and Meteorology Study. Slant column densities (SCDs) of NO2 and O4 were determined using the standard DOAS technique. Using a radiative transfer model and the O4 SCDs, aerosol optical depths were determined for clear sky conditions and compared to OMI, MODIS, AERONET, and local PM2.5 measurements. This aerosol information was input to a radiative transfer model to calculate NO2 air mass factors, which were fit to the measured NO2 SCDs to determine tropospheric vertical column densities (VCDs) of NO2. The method of determining NO2 VCDs in this way was validated for the first time by comparison to composite VCDs derived from aircraft and ground-based measurements of NO2. The new VCDs were compared to VCDs of NO2 determined via retrievals from the satellite instruments SCIAMACHY and OMI, for overlapping time periods. The satellite-derived VCDs were higher, with a mean bias of +0.5–0.9×1015 molec cm−2. This last finding is different from previous studies whereby MAX-DOAS geometric VCDs were higher than satellite determinations, albeit for urban areas with higher VCDs. An effective boundary layer height, BLHeff, is defined as the ratio of the tropospheric VCD and the ground level concentration of NO2. Variations of BLHeff can be linked to time of day, source region, stability of the atmosphere, and the presence or absence of elevated NOx sources. In particular, a case study is shown where a high VCD and BLHeff were observed when an elevated industrial plume of NOx and SO2 was fumigated to the surface as a lake breeze impacted the measurement site. High BLHeff values (~1.9 km) were observed during a regional smog event when high winds from the SW and high convection promoted mixing throughout the boundary layer. During this event, the regional line flux of NO2 through the region was estimated to be greater than 112 kg NO2 km−1 h−1.

With the increasing availability of observational data from different sources at a global level, joint analysis of these data is becoming especially attractive. For such an analysis – oftentimes with little prior knowledge about local and global interactions between the different observational variables at hand – an exploratory, data-driven analysis of the data may be of particular relevance. In the present work we used generalized additive models (GAM) in an exemplary study of spatio-temporal patterns in the tropospheric NO2-distribution derived from GOME satellite observations (1996 to 2001) at global scale. We focused on identifying correlations between NO2 and local wind fields, a quantity which is of particular interest in the analysis of spatio-temporal interactions. Formulating general functional, parametric relationships between the observed NO2 distribution and local wind fields, however, is difficult – if not impossible. So, rather than following a model-based analysis testing the data for predefined hypotheses (assuming, for example, sinusoidal seasonal trends), we used a GAM with non-parametric model terms to learn this functional relationship between NO2 and wind directly from the data. The NO2 observations showed to be affected by wind-dominated processes over large areas. We estimated the extent of areas affected by specific NO2 emission sources, and were able to highlight likely atmospheric transport "pathways". General temporal trends which were also part of our model – weekly, seasonal and linear changes – showed to be in good agreement with previous studies and alternative ways of analysing the time series. Overall, using a non-parametric model provided favorable means for a rapid inspection of this large spatio-temporal NO2 data set, with less bias than parametric approaches, and allowing to visualize dynamical processes of the NO2 distribution at a global scale.

Zenith-sky scattered sunlight observations using differential optical absorption spectroscopy (DOAS) technique were carried out in Shanghai, China (31.3° N, 121.5° E) since December 2006. At this polluted urban site, the measurements provided NO2 total columns in the daytime. Here, we present a new method to extract time series of tropospheric vertical column densities (VCDs) of NO2 from these observations. The derived tropospheric NO2 VCDs are important quantities for the estimation of emissions and for the validation of satellite observations. Our method makes use of assumptions on the relative NO2 height profiles and the diurnal variation of stratospheric NO2 VCDs. The main error sources arise from the uncertainties in the estimated stratospheric slant column densities (SCDs) and the determination of tropospheric NO2 air mass factor (AMF). For a polluted site like Shanghai, the accuracy of our method is conservatively estimated to be

In many investigations of tropospheric chemistry information about the two dimensional distribution of trace gases on a small scale (e.g. tens to hundreds of metres) is highly desirable. An airborne instrument based on imaging Differential Optical Absorption Spectroscopy has been built to map the two dimensional distribution of a series of relevant trace gases including NO2, HCHO, C2H2O2, H2O, O4, SO2, and BrO on a scale of 100 m. Here we report on the first tests of the novel aircraft instrument over the industrialised South African Highveld, where large variations in NO2 column densities in the immediate vicinity of several sources e.g. power plants or steel works, were measured. The observed patterns in the trace gas distribution are interpreted with respect to flux estimates, and it is seen that the fine resolution of the measurements allows separate sources in close proximity to one another to be distinguished.

A first direct intercomparison of aerosol vertical profiles from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations, performed during the Cabauw Intercomparison Campaign of Nitrogen Dioxide measuring Instruments (CINDI) in summer 2009, is presented. Five out of 14 participants of the CINDI campaign reported aerosol extinction profiles and aerosol optical thickness (AOT) as deduced from observations of differential slant column densities of the oxygen collision complex (O4) at different elevation angles. Aerosol extinction vertical profiles and AOT are compared to backscatter profiles from a ceilometer instrument and to sun photometer measurements, respectively. Furthermore, the near-surface aerosol extinction coefficient is compared to in situ measurements of a humidity-controlled nephelometer and dry aerosol absorption measurements. The participants of this intercomparison exercise use different approaches for the retrieval of aerosol information, including the retrieval of the full vertical profile using optimal estimation and a parametrised approach with a prescribed profile shape. Despite these large conceptual differences, and also differences in the wavelength of the observed O4 absorption band, good agreement in terms of the vertical structure of aerosols within the boundary layer is achieved between the aerosol extinction profiles retrieved by the different groups and the backscatter profiles observed by the ceilometer instrument. AOTs from MAX-DOAS and sun photometer show a good correlation (R>0.8), but all participants systematically underestimate the AOT. Substantial differences between the near-surface aerosol extinction from MAX-DOAS and from the humidified nephelometer remain largely unresolved.

A new method for the satellite remote sensing of different types of vegetation and ocean colour is presented. In contrast to existing algorithms relying on the strong change of the reflectivity in the red and near infrared spectral region, our method analyses weak narrow-band (few nm) reflectance structures (i.e. "fingerprint" structures) of vegetation in the red spectral range. It is based on differential optical absorption spectroscopy (DOAS), which is usually applied for the analysis of atmospheric trace gas absorptions. Since the spectra of atmospheric absorption and vegetation reflectance are simultaneously included in the analysis, the effects of atmospheric absorptions are automatically corrected (in contrast to other algorithms). The inclusion of the vegetation spectra also significantly improves the results of the trace gas retrieval. The global maps of the results illustrate the seasonal cycles of different vegetation types. In addition to the vegetation distribution on land, they also show patterns of biological activity in the oceans. Our results indicate that improved sets of vegetation spectra might lead to more accurate and more specific identification of vegetation type in the future.

Measurements from the Global Ozone Monitoring Experiment (GOME) are used to study the chemical evolution of the stratosphere during the unusual 2002 winter in the Southern Hemisphere. The results show that chlorine activation as indicated by OClO columns was similar to previous years in the vortex until the major warming on 26 September 2002 after which it decreased rapidly. Similarly, NO2 columns were only slightly larger than in previous years before the warming, indicating strong denoxification and probably also denitrification. After the warming, very large NO2 columns were observed for a few days, which then decreased again as the vortex reestablished itself until the final warming. Ozone columns were much larger than in any previous year from September onward, mainly as a result of the unusual dynamical situation. Analysis of the global long-term time series of GOME measurements since 1996 provides a unique opportunity to set the austral winter 2002 into perspective. The GOME data reveal the large difference in variability of chlorine activation between the two hemispheres, whereas denoxification shows surprisingly little variation from year to year in both hemispheres. However, NO2 depletion in the Southern Hemisphere is usually sustained for about one month longer in the Antarctic stratosphere as a result of the stable vortex. Compared to the observations in the Northern Hemisphere, the austral winter 2002 was still stable and cold and had a high potential for chemical ozone destruction.

In this article, we present satellite observations of atmospheric sulfur dioxide (SO_2) from volcanic eruptions. Global ozone monitoring experiment (GOME) data for the years 1996–2002 is analyzed using a DOAS based algorithm with the aim of retrieving SO_2 slant column densities (SCD). The retrieval of SO_2 SCD in the UV spectral region is difficult due to strong and interfering ozone absorptions. It is also likely affected by instrumental effects. We investigated these effects in detail to obviate systematic biases in the SO_2 retrieval. A quantitative study of about 20 volcanoes from Italy, Iceland, Congo/Zaire, Ecuador, Japan, Vanuatu Island and Mexico is presented. The focus is on both eruption and out gassing scenarios. We prepared a 7-year mean map (1996–2002) of SO_2 SCD observed by GOME and tabulated the ratios of the maximum SO_2 SCD observed to the average SO_2 SCD as seen in the 7-year mean map. The further aim of this study is to provide information about unknown volcanic eruptions, e.g., Bandai Honshu Japan, Central Islands Vanuatu, Piton de la Fournaise Reunion Island France, Kamchatka region of Russia and from Indonesia especially. The results demonstrate a high sensitivity of the GOME instrument towards SO_2 emissions during both eruption and degassing episodes.

The Global Ozone Monitoring Experiment (GOME) allows the retrieval of tropospheric vertical column densities (VCDs) of NO2 on a global scale. Regions with enhanced industrial activity can clearly be detected, but the standard spatial resolution of the GOME ground pixels (320x40km2) is insufficient to resolve regional trace gas distributions or individual cities. Every 10 days within the nominal GOME operation, measurements are executed in the so called narrow swath mode with a much better spatial resolution (80x40km2). We use this data (1997-2001) to construct a detailed picture of the mean global tropospheric NO2 distribution. Since - due to the narrow swath - the global coverage of the high resolution observations is rather poor, it has proved to be essential to deseasonalize the single narrow swath mode observations to retrieve adequate mean maps. This is done by using the GOME backscan information. The retrieved high resolution map illustrates the shortcomings of the standard size GOME pixels and reveals an unprecedented wealth of details in the global distribution of tropospheric NO2. Localised spots of enhanced NO2 VCD can be directly associated to cities, heavy industry centers and even large power plants. Thus our result helps to check emission inventories. The small spatial extent of NO2 "hot spots" allows us to estimate an upper limit of the mean lifetime of boundary layer NOx of 17h on a global scale. The long time series of GOME data allows a quantitative comparison of the narrow swath mode data to the nominal resolution. Thus we can analyse the dependency of NO2 VCDs on pixel size. This is important for comparing GOME data to results of new satellite instruments like SCIAMACHY (launched March 2002 on ENVISAT), OMI (launched July 2004 on AURA) or GOME II (to be launched 2005) with an improved spatial resolution.

Forest fire emissions have a strong impact on the concentrations of trace gases and aerosols in the atmosphere. In order to quantify the influence of boreal forest fire emissions on the atmospheric composition, the fire seasons of 1997 and 1998 are compared in this paper. Fire activity in 1998 was very strong, especially over Canada and Eastern Siberia, whereas it was much weaker in 1997. According to burned area estimates the burning in 1998 was more than six times as intense as in 1997. Based on hot spot locations derived from ATSR (Along Track Scanning Radiometer) data and official burned area data, fire emissions were estimated and their transport was simulated with a Lagrangian tracer transport model. Siberian and Canadian forest fire tracers were distinguished to investigate the transport of both separately. The fire emissions were transported even over intercontinental distances. Due to the El Niño induced meteorological situation, transport from Siberia to Canada was enhanced in 1998. Siberian fire emissions were transported towards Canada and contributed concentrations more than twice as high as those due to Canada's own CO emissions by fires. In 1998 both tracers arrive at higher latitudes over Europe, which is due to a higher North Atlantic Oscillation (NAO) index in 1998. The simulated emission plumes are compared to CMDL (Climate Monitoring and Diagnostics Laboratory) CO2 and CO data, Total Ozone Mapping Spectrometer (TOMS) aerosol index (AI) data and Global Ozone Monitoring Experiment (GOME) tropospheric NO2 and HCHO columns. All the data show clearly enhanced signals during the burning season of 1998 compared to 1997. The results of the model simulation are in good agreement with ground-based as well as satellite-based measurements.

In this article, we present satellite observations of OClO from the years 1995–2002. The focus is on observations of OClO in the Arctic wintertime stratosphere, which are compared to results of the SLIMCAT model and to observations in the Antarctic. In particular, we investigated the beginning and ending of the chlorine activation in the Arctic stratosphere. The Slant Column Densities (SCDs) of OClO increase significantly, when the temperature falls below the threshold for formation of Polar Stratospheric Clouds. The time for decrease of the OClO-SCDs in the deactivation phase (early spring) varies strongly and is related to the degree of denitrification. In the Arctic, chlorine activation can be further increased when there is strong activity of stratospheric mountain waves.

Nitrogen oxides (NO + NO 2 =NO x ) are important trace gases in the troposphere with impact on human health, climate and atmospheric chemistry, e.g. through their role in ozone production. Therefore a better understanding of the strength of the various sources (fossil fuel combustion, biomass burning, soil emissions, lightning) is desirable. NO x produced by lightning contributes approx. 12%, i.e. 5 (2–20) T g [N]/year [Atmos. Environ. 31 (1997) 1735; EULINOX – The European Lightning Nitrogen Oxides Project. DLR – Forschungsbericht 2000-28, 2000], of the totally produced nitrogen oxides. An uncertainty of one order of magnitude remains. Here we present an estimation of lightning produced NO x using satellite data. Lightning activity is monitored by the Lightning Imaging Sensor since November 1997. The same time span is also covered by NO 2 measurements from the Global Ozone Monitoring Experiment. This allows a statistical approach. In this study we relate lightning frequency and the tropospheric vertical column densities of NO 2 over Central Australia, where other NO x sources have only minor contribution. By analyzing the correlation of lightning activity with the vertical column densities of NO 2 we estimate the globally produced lightning NO x to be ∼2.8 (0.8–14) T g [N]/year. Despite the many uncertainties involved in NO 2 retrieval (e.g. profile information, cloud influence), this value shows a good agreement with literature.

In this paper we present data on the variation of tropospheric BrO, that is connected with the spring time ozone depletion in polar regions. For this study we use data derived from the Global Ozone Monitoring Experiment (GOME) for the years 1996–2001. We especially focus on the possible detection of trends in the extent of coverage of polar regions by BrO and on the time series of BrO abundances. For this purpose we calculated monthly means during polar spring of the areas that are covered with BrO exceeding certain thresholds. It turns out that in the timeseries of total, i.e. tropospheric and stratospheric, BrO column densities there is, up to now, no clear trend identifiable. In contrast, the analysis of areas covered by high concentrations of tropospheric BrO (columns >5.5 × 1013 molecules/cm2) is considerably expanding (about 10% per year during 1996–2000) in the northern hemisphere in the comparison of monthly means during polar spring, which is possibly due to an anthropogenic effect on the climate system.

Nitrogen oxides (NO+NO2=NOx) are important trace gases in the troposphere with impact on human health, atmospheric chemistry and climate. Besides natural sources (lightning, soil emissions) and biomass burning, fossil fuel combustion is estimated to be responsible for about 50\\% of the total production of NOx. Since human activity in industrialized countries largely follows an artificial seven-day cycle, fossil fuel combustion is expected to be reduced during weekends. This "weekend effect" is well known from local, ground based measurements, but has never been analysed on a global scale before. The Global Ozone Monitoring Experiment (GOME) on board the ESA-satellite ERS-2 allows measurements of NO2 column densities. Applying sophisticated algorithms, vertical column densities (VCD) of tropospheric NO2 can be determined. We demonstrate the statistical analysis of weekly cycles of tropospheric NO2 VCDs for different regions of the world. In the cycles of the industrialized regions and cities in the US, Europe and Japan a clear Sunday minimum of tropospheric NO2 VCD can be seen. Sunday NO2 VCDs are about 25–50% lower than working day levels. Metropolitan areas with other religious and cultural backgrounds (Jerusalem, Mecca) show different weekly patterns corresponding to different days of rest. In China, no weekly pattern can be found. The presence of a weekly cycle in the measured tropospheric NO2 VCD allows the identification of anthropogenic sources. In addition, the fraction of emissions subjected to a weekly cycle (mainly transport, power generation) with respect to a constant background (all kind of natural sources, biomass burning, heavy industry) can be estimated. Furthermore, we estimated the lifetime of tropospheric NO2 by analysing the mean weekly cycle over Germany in detail, obtaining a value of about 12 h.

This paper studies the interannual variability of pollution pathways from northern hemisphere (NH) continents into the Arctic. Using a 15-year model simulation of the dispersion of passive tracers representative of anthropogenic emissions from NH continents, we show that the North Atlantic Oscillation (NAO) exerts a strong control on the pollution transport into the Arctic, particularly in winter and spring. For tracer lifetimes of 5 (30) days, surface concentrations in the Arctic winter are enhanced by about 70% (30%) during high phases of the NAO (in the following referred to as NAO+) compared to its low phases (NAO-). This is mainly due to great differences in the pathways of European pollution during NAO+ and NAO- phases, respectively, but reinforced by North American pollution, which is also enhanced in the Arctic during NAO+ phases. In contrast, Asian pollution in the Arctic does not significantly depend on the NAO phase. The model results are confirmed using remotely-sensed NO2 vertical atmospheric columns obtained from seven years of satellite measurements, which show enhanced northward NO2 transport and reduced NO2 outflow into the North Atlantic from Central Europe during NAO+ phases. Surface measurements of carbon monoxide (CO) and black carbon at high-latitude stations further corroborate the overall picture of enhanced Arctic pollution levels during NAO+ phases

International audience; Published by Copernicus Publications on behalf of the European Geosciences Union. 9578 M. Beekmann et al.: Evidence for a dominant regional contribution to fine particulate matter levels Abstract. A detailed characterization of air quality in the megacity of Paris (France) during two 1-month intensive campaigns and from additional 1-year observations revealed that about 70 % of the urban background fine particulate matter (PM) is transported on average into the megacity from upwind regions. This dominant influence of regional sources was confirmed by in situ measurements during short intensive and longer-term campaigns, aerosol optical depth (AOD) measurements from ENVISAT, and modeling results from PMCAMx and CHIMERE chemistry transport models. While advection of sulfate is well documented for other megacities, there was surprisingly high contribution from long-range transport for both nitrate and organic aerosol. The origin of organic PM was investigated by comprehensive analysis of aerosol mass spectrometer (AMS), radio-carbon and tracer measurements during two intensive campaigns. Primary fossil fuel combustion emissions constituted less than 20 % in winter and 40 % in summer of carbonaceous fine PM, unexpectedly small for a megacity. Cooking activities and, during winter, residential wood burning are the major primary organic PM sources. This analysis suggests that the major part of secondary organic aerosol is of modern origin , i.e., from biogenic precursors and from wood burning. Black carbon concentrations are on the lower end of values encountered in megacities worldwide, but still represent an issue for air quality. These comparatively low air pollution levels are due to a combination of low emissions per inhabitant , flat terrain, and a meteorology that is in general not conducive to local pollution build-up. This revised picture of a megacity only being partially responsible for its own average and peak PM levels has important implications for air pollution regulation policies.

From June to July 2009 more than thirty different in-situ and remote sensing instruments from all over the world participated in the Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI). The campaign took place at KNMI's Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands. Its main objectives were to determine the accuracy of state-of-the-art ground-based measurement techniques for the detection of atmospheric nitrogen dioxide (both in-situ and remote sensing), and to investigate their usability in satellite data validation. The expected outcomes are recommendations regarding the operation and calibration of such instruments, retrieval settings, and observation strategies for the use in ground-based networks for air quality monitoring and satellite data validation. Twenty-four optical spectrometers participated in the campaign, of which twenty-one had the capability to scan different elevation angles consecutively, the so-called Multi-axis DOAS systems, thereby collecting vertical profile information, in particular for nitrogen dioxide and aerosol. Various in-situ samplers and lidar instruments simultaneously characterized the variability of atmospheric trace gases and the physical properties of aerosol particles. A large data set of continuous measurements of these atmospheric constituents has been collected under various meteorological conditions and air pollution levels. Together with the permanent measurement capability at the CESAR site characterizing the meteorological state of the atmosphere, the CINDI campaign provided a comprehensive observational data set of atmospheric constituents in a highly polluted region of the world during summertime. First detailed comparisons performed with the CINDI data show that slant column measurements of NO2, O4 and HCHO with MAX-DOAS agree within 5 to 15%, vertical profiles of NO2 derived from several independent instruments agree within 25% of one another, and MAX-DOAS aerosol optical thickness agrees within 20–30% with AERONET data. For the in-situ NO2 instrument using a molybdenum converter, a bias was found as large as 5 ppbv during day time, when compared to the other in-situ instruments using photolytic converters.

In the field, aerosol in-situ measurements are often performed under dry conditions (relative humidity RHsp(λ) was measured dry and at various, predefined RH conditions between 20 and 95% with a humidified nephelometer. The scattering enhancement factor f(RH,λ) is the key parameter to describe the effect of RH on σsp(λ) and is defined as σsp(RH,λ) measured at a certain RH divided by the dry σsp(dry,λ). The measurement of f(RH,λ) together with the dry absorption measurement (assumed not to change with RH) allows the determination of the actual extinction coefficient σep(RH,λ) at ambient RH. In addition, a wide range of other aerosol properties were measured in parallel. The measurements were used to characterize the effects of RH on the aerosol optical properties. A closure study showed the consistency of the aerosol in-situ measurements. Due to the large variability of air mass origin (and thus aerosol composition) a simple parameterization of f(RH,λ) could not be established. If f(RH,λ) needs to be predicted, the chemical composition and size distribution need to be known. Measurements of four MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments were used to retrieve vertical profiles of σep(λ). The values of the lowest layer were compared to the in-situ values after conversion of the latter ones to ambient RH. The comparison showed a good correlation of R2 = 0.62–0.78, but the extinction coefficients from MAX-DOAS were a factor of 1.5–3.4 larger than the in-situ values. Best agreement is achieved for a few cases characterized by low aerosol optical depths and low planetary boundary layer heights. Differences were shown to be dependent on the applied MAX-DOAS retrieval algorithm. The comparison of the in-situ extinction data to a Raman LIDAR (light detection and ranging) showed a good correlation and higher values measured by the LIDAR (R2 = 0.82−0.85, slope of 1.69–1.76) if the Raman retrieved profile was used to extrapolate the directly measured extinction coefficient to the ground. The comparison improved if only nighttime measurements were used in the comparison (R2 = 0.96, slope of 1.12).

In this study, we analyse the sensitivity of nadir viewing satellite observations in the visible range to freshly produced lightning NOx. This is a particular challenge due to the complex and highly variable conditions of meteorology, (photo-) chemistry, and radiative transfer in and around cumulonimbus clouds. For the first time, such a study is performed accounting for photo-chemistry, dynamics, and radiative transfer in a consistent way: A one week episode in the TOGA COARE/CEPEX region (Pacific) in December 1992 is simulated with a 3-D cloud resolving chemistry model. The simulated hydrometeor mixing ratios are fed into a Monte Carlo radiative transfer model to calculate box-Air Mass Factors (box-AMFs) for NO2. From these box-AMFs, together with model NOx profiles, slant columns of NO2 (SNO2), i.e. synthetic satellite measurements, are calculated and set in relation to the actual model NOx vertical column (VNOx), yielding the "sensitivity" SNO2/VNOx. From this study, we find a mean sensitivity of 0.46. NOx below the cloud bottom is mostly present as NO2, but shielded from the satellites' view, whereas NOx at the cloud top or above is shifted to NO due to high photolysis and low temperature, and hence not detectable from space. However, a significant fraction of the lightning produced NOx in the middle part of the cloud is present as NO2 and has a good visibility from space. Due to the resulting total sensitivity being quite high, nadir viewing satellites provide a valuable additional platform to quantify NOx production by lightning; strong lightning events over "clean" regions should be clearly detectable in satellite observations. Since the observed enhancement of NO2 column densities over mesoscale convective systems are lower than expected for current estimates of NOx production per flash, satellite measurements can in particular constrain the upper bound of lightning NOx production estimates.

Cloud climate feedback constitutes the most important uncertainty in climate modelling, and currently even its sign is still unknown. In the recently published report of the intergovernmental panel on climate change (IPCC), 6 out of 20 climate models showed a positive and 14 a negative cloud radiative feedback in a doubled CO2 scenario. The radiative budget of clouds has also been investigated by experimental methods, especially by studying the relation of satellite observed broad band shortwave and longwave radiation to sea surface temperature. Here we present a new method for the investigation of the dependence of cloud properties on temperature changes, derived from spectrally resolved satellite observations in the visible spectral range. Our study differs from previous investigations in three important ways: first, we directly extract cloud properties (effective cloud fraction and effective cloud top height) and relate them to surface temperature. Second, we retrieve the cloud altitude from the atmospheric O2 absorption instead from thermal IR radiation. Third, our correlation analysis is performed using 7.5 years of global monthly anomalies (with respect to the average of the same month for all years). For most parts of the globe (except the tropics) we find a negative correlation of effective cloud fraction versus surface-near temperature. In contrast, for the effective cloud top height a positive correlation is found for almost the whole globe. Both findings might serve as an indicator for an overall positive cloud radiative feedback. Another peculiarity of our study is that the cloud-temperature relationships are determined for fixed locations (instead to spatial variations over selected areas) and are based on the "natural" variability over several years (instead the anomaly for a strong El-Nino event). From a detailed comparison to cloud properties from the International Satellite Cloud Climatology Project (ISCCP), in general good agreement is found. However, also systematic differences occurred indicating that our results provide independent and complementary information on cloud properties. Climate models should thus aim to reproduce our findings. Recommendations for the development of a "processor" to convert model results into the cloud sensitive quantities observed by the satellite are given.

[1] We have analyzed global trends of total column precipitable water from measurements of the Global Ozone Monitoring Experiment (GOME) on the European Research Satellite (ERS-2) for the period January 1996 to June 2003. In contrast to other satellite retrieval methods of total column precipitable water, our analysis does not rely on a priori assumptions or additional information; thus it is particularly well suited to trend studies. The chosen wavelength range in the red spectral region ensures similar sensitivity for observations over land and ocean and thus a consistent global picture. To minimize the influence of clouds on the water vapor trends, we selected observations under mainly clear-sky conditions. The temporal evolution of the monthly or yearly averaged total column precipitable water, especially in the tropics, is highly correlated to that of the near-surface temperature, indicating that the global atmospheric humidity is mainly driven by Clausius-Clapeyron's principle. The magnitude of the dependence on near-surface temperature indicates a strong water vapor feedback. The spatial patterns of the water vapor trends show both positive and negative signs. Especially over the oceans, trend patterns very similar to those of near-surface temperature are found. In contrast, over Northern Hemispheric continents the trend patterns are much less correlated, and even opposite trends for water vapor and the near-surface temperatures are found. During the period 1996–2002 the globally and yearly averaged total column precipitable water increased by 2.8 ± 0.8% (excluding the ENSO period).

[1] Nitrogen oxides play a key role in tropospheric chemistry; to study the distribution patterns of the corresponding anthropogenic emissions ( fossil, industrial, waste), we use three independent data sources: GOME measurements of the tropospheric NO2 column density fields, the EDGAR 3 emission inventory as an estimation of the anthropogenic NOx emissions and nighttime images of worldwide human settlements seen by the DMSP OLS satellite instrument as a proxy for these emission patterns. The uncertainties are not known precisely for any of the fields. Using the MOZART-2 CTM, tropospheric column density fields are calculated from the emission estimates, and transformations are developed to turn the GOME columns into anthropogenic emission fields. Assuming the errors of the three data sources ( GOME, EDGAR, lights) to be independent, we are able to determine ranges for the pattern errors of the column density fields and values for the pattern errors of the source fields by a correlation analysis that connects relative error (co) variances and correlation coefficients. That method was developed for this investigation but can generally be used to calculate relative error variances of data sets, if the errors of at least three of them can be assumed to be independent. We estimate the pattern error of the EDGAR 3 anthropogenic NOx emission field as ( 27 +/- 5)%, which can be reduced by combining all fields to ( 15 +/- 3)%. By determining outliers, we identify locations with high uncertainty that need further examination.

Nitrogen oxides (NOx=NO+NO2) play an important role in tropospheric chemistry, in particular in catalytic ozone production. Lightning provides a natural source of nitrogen oxides, dominating the production in the tropical upper troposphere, with strong impact on tropospheric ozone and the atmosphere's oxidizing capacity. Recent estimates of lightning produced NOx (LNOx) are of the order of 5 Tg [N] per year with still high uncertainties in the range of one order of magnitude. The Global Ozone Monitoring Experiment (GOME) on board the ESA-satellite ERS-2 allows the retrieval of tropospheric vertical column densities (TVCDs) of NO2 on a global scale. Here we present the GOME NO2 measurement directly over a large convective system over the Gulf of Mexico. Simultaneously, cloud-to-ground (CG) flashes are counted by the U.S. National Lightning Detection Network (NLDNTM), and extrapolated to include intra-cloud (IC)+CG flashes based on a climatological IC:CG ratio derived from NASA's space-based lightning sensors. A series of 14 GOME pixels shows largely enhanced TVCDs over thick and high clouds, coinciding with strong lightning activity. The enhancements can not be explained by transport of anthropogenic NOx and must be due to fresh production of LNOx. A quantitative analysis, accounting in particular for the visibility of LNOx from satellite, yields a LNOx production of 77 (27–230) moles of NOx, or 1.1 (0.4–3.2) kg [N], per flash. If simply extrapolated, this corresponds to a global LNOx production of 1.5 (0.5–4.5) Tg [N]/yr.

[1] Global data sets of total column precipitable water and cloud cover derived from the Global Ozone Monitoring Experiment (GOME) are analyzed with respect to anomalies induced by the strong El Nino 1997/1998. In contrast to other satellite observations of water vapor, the GOME nadir observations in the visible spectral range are of similar sensitivity over both land and ocean. In addition, they are sensitive in particular to the water vapor concentration close to the surface where a major fraction of the water vapor column is present. Information on the atmospheric cloud cover was derived from the observed broadband intensity as well as the oxygen (O2) absorption. While the first quantity is mainly a measure of geometrical cloud fraction, the latter also yields information on the cloud altitude. We investigated the time series of monthly mean values as well as anomalies calculated for a 6-month period during the El Nino 1997/1998. For all three quantities we found strong anomalies over large areas and for extended periods. Especially for the total column precipitable water, significant anomalies were found even in mid and high latitudes indicating substantial changes in the hydrological cycle and the global circulation patterns.

[1] We describe the retrieval of stratospheric NO2 vertical column densities from the Global Ozone Monitoring Experiment (GOME) aboard the ERS-2 satellite. Different differential optical absorption spectroscopy (DOAS) evaluations are compared in order to investigate uncertainties caused by the diffuser plate. An improved version of our algorithm to separate the tropospheric and stratospheric fraction of NO2 from GOME satellite data is described and is used to extract a long term data set of stratospheric NO2 (1996–2000). In addition, the average seasonal variation in the global distribution is determined, which allows us to monitor and investigate specific aspects of stratospheric chemistry, in particular the interhemispheric comparison of stratospheric NO2. In contrast to other satellite observations (e.g., SAGE II, OSIRIS), GOME observations of stratospheric NO2 include the lower stratosphere. In general, our observations are in agreement with previous measurements and confirm the current knowledge of stratospheric nitrogen chemistry.