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We present a long-term data set of 1∘×1∘ monthly mean total column water vapour (TCWV) based on global measurements of the Ozone Monitoring Instrument (OMI) covering the time range from January 2005 to December 2020. In comparison to the retrieval algorithm of Borger et al. (2020), several modifications and filters have been applied accounting for instrumental issues (such as OMI's “row anomaly”) or the inferior quality of solar reference spectra. For instance, to overcome issues related to low-quality reference spectra, the daily solar irradiance spectrum is replaced by an annually varying mean earthshine radiance obtained in December over Antarctica. For the TCWV data set, we only consider measurements with an effective cloud fraction less than 20 %, an air mass factor (AMF) greater than 0.1, a snow- and ice-free ground pixel, and an OMI row that is not affected by the row anomaly over the complete time range of the data set. The individual TCWV measurements are then gridded to a regular 1∘×1∘ lattice, from which the monthly means are calculated. The investigation of sampling errors in the OMI TCWV data set shows that these are dominated by the clear-sky bias and cause on average deviations of around −10 %, which is consistent with the findings of previous studies. However, the spatiotemporal sampling errors and those due to the row-anomaly filter are negligible. In a comprehensive intercomparison study, we demonstrate that the OMI TCWV data set is in good agreement with the global reference data sets of ERA5 (fifth-generation ECMWF atmospheric reanalysis), RSS SSM/I (Remote Sensing Systems Special Sensor Microwave Imager), and CM SAF/CCI TCWV-global (COMBI): over ocean the orthogonal distance regressions indicate slopes close to unity with very small offsets and high coefficients of determination of around 0.96. However, over land, distinctive positive deviations of more than +10 kg m−2 are obtained for high TCWV values. These overestimations are mainly due to extreme overestimations of high TCWV values in the tropics, likely caused by uncertainties in the retrieval input data (surface albedo, cloud information) due to frequent cloud contamination in these regions. Similar results are found from intercomparisons with in situ radiosonde measurements from version 2 of the Integrated Global Radiosonde Archive (IGRA2) data set. Nevertheless, for TCWV values smaller than 25 kg m−2, the OMI TCWV data set shows very good agreement with the global reference data sets. Furthermore, a temporal stability analysis proves that the OMI TCWV data set is consistent with the temporal changes in the reference data sets and shows no significant deviation trends. As the TCWV retrieval can be easily applied to further satellite missions, additional TCWV data sets can be created from past missions, such as the Global Ozone Monitoring Experiment-1 (GOME-1) or the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY); under consideration of systematic differences (e.g. due to different observation times), these data sets can be combined with the OMI TCWV data set in order to create a data record that would cover a time span from 1995 to the present. Moreover, the TCWV retrieval will also work for all missions dedicated to NO2 in the future, such as Sentinel-5 on MetOp-SG. The Max Planck Institute for Chemistry (MPIC) OMI total column water vapour (TCWV) climate data record (CDR) is available at https://doi.org/10.5281/zenodo.7973889 (Borger et al., 2023).

Bromine monoxide (BrO) is a key radical in the atmosphere, influencing the chemical state of the atmosphere, most notably the abundance of ozone. The main effect of BrO onto tropospheric ozone concentrations occurs in bromine release events in polar regions, salt pans and volcanic plumes. Ozone depletion caused by halogen release has been observed and modeled for such conditions, in particular inside volcanic plumes. Furthermore, the molar bromine to sulphur ratio in volcanic plumes is a proxy for the magmatic composition of a volcano and potentially an eruption forecast parameter. The integrated column of BrO in the atmosphere, which in turn serves as an estimate for the bromine content, can be detected simultaneously with SO2 via spectroscopic measurements using the Differential Optical Absorption Spectroscopy (DOAS). Thus, a direct derivation of the BrO/SO2 ratio can be performed from a single measurement. Satellite spectroscopic observations offer the potential to observe and monitor volcanic bromine release globally. The detection of BrO in volcanic plumes is limited by the precision and sensitivity of the retrieval, which so far only allowed for the detection of BrO during major eruptions, leading to a potential sampling bias when looking at the BrO/SO2 ratio. The The TROPospheric Monitoring Instrument (TROPOMI) onboard Sentinel-5 Precursor (S-5P) however, with its unprecedented spatial resolution of up to 3.5 × 5.5 km2 and high signal-to-noise ratio, enables the detection of BrO in minor eruptions or even quiescent degassing. In this study, we investigate, how far the BrO retrieval can be improved using TROPOMI data and how well BrO can be detected, even in small eruptions and during quiescent volcanic degassing. There are two steps, for which improvements in accuracy are investigated and applied: the improvement and quantitative determination of (1) the detection limit of the DOAS BrO column retrieval and (2) the correction of non-volcanic background BrO signal. First, the DOAS retrieval settings are varied and their influence on accuracy and precision is investigated with respect to the detection limit and potential systematic influences. Based on these results, we propose a dedicated DOAS evaluation scheme optimized for the detection of BrO in volcanic plumes. For the DOAS retrieval, we propose the use of a large fit window from 323–360 nm, yielding a factor of 1.8 lower statistical uncertainty compared to previous BrO DOAS algorithms, while not enhancing systematic influences. Second, the effect of the background BrO is reduced by a latitude dependent empirical correction scheme correlated to cloud information as well as information on the ozone column. Via these improvements, the combined statistical and systematic uncertainties of the resulting BrO vertical column density is in the order of 7 × 1012 molecules cm−2, which allows for the detection of even slightly enhanced BrO amounts inside minor eruptive plumes of bromine-rich volcanoes.

NO2 is an important air pollutant and has been recognized for its hazardous impact on human health. Although routine in-situ measurements of NO2 are available in many regions of the earth, models for regional chemistry and transport (RCT) are often used to predict trace gas concentrations where no direct measurements are available. An important aspect of realistic NO2 modelling is to use accurate NOx emissions with high temporal resolution. The standard practice is to use a monthly or yearly resolved emission inventory in combination with sector-specific hourly emission weights (“temporal profiles”) in order to simulate diurnal, weekly, and seasonal emission patterns. Temporal profiles are typically derived from empirical data, e.g. car counts on highways, and have been known to improve RCT simulations significantly. Nonetheless, in comparison against in-situ measurements, simulated NO2 concentrations are usually too low at daytime and too high at nighttime, with relative deviations of up to 50 %. This hints towards faulty temporal emission profiles.We present a novel method to determine improved temporal emission profiles for NOx emissions in a WRF-Chem simulation for May 2019 in central Europe. The temporal profiles are determined in an iterative procedure that consists of running the simulation, comparing the simulated NOx concentrations to in-situ reference measurements, and adjusting the hourly temporal profiles to compensate deviations between simulation and reference values. In a subsequent intercomparison of model results with observational datasets (surface concentrations from in-situ measurements, tropospheric vertical column densities from the TROPOMI satellite instrument, and concentration profiles from MAX-DOAS retrievals), we validate our simulation results. In particular, the typical NO2 underestimation at noontime is resolved and the monthly average of simulated vertical column densities deviates less than 7% from the TROPOMI reference data.

We map high-resolution nitrogen oxides (NOx) emissions in US cities from the retrieved TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO2) columns. A new database of gridded emissions at a horizontal spatial resolution of 0.05°×0.05° has been developed using our newly-developed CTM-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM). We validate the accuracy of MISATEAM using synthetic NO2 observations derived from the NASA-Unified Weather Research and Forecasting (NU-WRF) model at a horizontal spatial resolution of 4 km × 4 km. The validation results demonstrate the excellent agreement between the inferred emissions magnitudes and the NU-WRF given ones with a correlation coefficient (R) of 0.99 and a normalized mean bias (NMB) of -0.08. They also show a consistent spatial pattern with R of 0.88 ± 0.06 for all investigated cities when comparing inferred and given emissions at grid level. The TROPOMI-based database derived in this study includes annual emission maps for 39 US large cities from 2018 to 2021. While there is a good agreement with national emission inventory (NEI) in general, there are noticeable differences in spatial pattern in some cases. The satellite-derived spatiotemporal patterns of NOx emissions complement information difficult to capture in the conventional emission inventories compiled with “bottom-up” methods by suggesting the misallocation of emissions and/or missing sources. We expect to extend the database globally and also include estimates based on NO2 observations from OMI to provide a longer time record. The method could also be applied to data from future geostationary satellites, such as Geostationary Environment Monitoring Spectrometer (GEMS) or the Tropospheric Emissions: Monitoring Pollution (TEMPO) instrument, to provide diurnal variations in NOx emissions.

Transit cruises of German research vessels across oceans provide a unique platform for MAX-DOAS measurements of atmospheric trace gases such as nitrogen dioxide (NO2), formaldehyde (HCHO) and sulphur dioxide (SO2). The Deep Blue/PORD campaign took place from 24 June to 21 July 2022. During that period the research vessel SONNE was crossing the Pacific in meridional direction from 22° S to 54° N in an area that is typically used as reference for satellite data due to its large distance from anthropogenic emission sources.In this study we focus on three trace gases: NO2 columns provide information on the meridional distribution of stratospheric NO2 as well as the distribution of tropospheric background NO2 above the marine boundary layer. For the analysis, high signal “peaks” that only last a short time are filtered as they most likely originate from the ship exhaust. First results show a minimum of total NO2 columns between the equator and about 15° N. HCHO and SO2 mainly appear as plumes from nearby islands and/or volcanoes in the Solomon Sea, where biogenic and volcanic activities are naturally high. In combination with the onboard instrumentation (Ceilometer, Pyranometer and a cloud camera) this data set provides a detailed description of the atmosphere along the cruise track.

Atmospheric water vapour plays a key role for the Earth's energy budget and temperature distribution via radiative effects and latent heat transport. Moreover, the distribution and transport of water vapour is closely linked to atmospheric dynamics on all spatiotemporal scales. In this context, monitoring of the water vapour distribution is essential for numerical weather prediction as well as for climate modelling.The Geostationary Environment Monitoring Spectrometer (GEMS) instrument on board the GEO-KOMPSAT-2B satellite offers new opportunities for observing and investigating the regional water vapour distribution over East Asia, especially phenomena such as typhoons or atmospheric rivers, and could thus represent another valuable data source, e.g. for nowcasting systems of natural hazards.In this study, we show the first total column water vapour (TCWV) results retrieved from GEMS UV/vis spectra based on the algorithm of Borger et al. (2020). In addition, we also present an update of the existing algorithm, which, for example, replaces the previous simplified determination of the a priori water vapour profile with a deep neural network. We also compare our results to different reference data sets from ground-based in situ and remote sensing observations, reanalysis models, and satellite measurements.

We report a newly developed global anthropogenic SO2 emission inventory. Within this study, SO2 measurements from the Tropospheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5P satellite have been used to detect and quantify SO2 emissions from point sources for the time range 2018-2022. Our algorithm derives the advection of SO2 by combining TROPOMI SO2 column densities and wind fields from ERA5, i.e. taking the product of vertical column densities and the horizontally projected wind speed. In addition, several corrections, e.g., for satellite sensitivity and topography are applied. The results will be compared to existing emission datasets.The study is part of the World Emission project funded by ESA and the complete SO2 emission inventory will be available via the World Emission Portal at https://app.world-emission.com.

Bromine monoxide (BrO) is a halogen radical influencing atmospheric chemical processes, in particular the abundance of ozone, e. g. in the polar boundary layer and above salt lakes, in the stratosphere as well as in volcanic plumes. Furthermore, the molar bromine to sulphur ratio in volcanic gas emissions is a proxy for the magmatic composition of a volcano and potentially an eruption forecast parameter.The high spatial resolution combined with the better signal-to-noise ratio of the S-5P/TROPOMI instrument (up to 3.5x5.5km2) and its daily global coverage offer the potential to detect BrO and its corresponding ratio with sulphur dioxide (BrO/SO2) even during minor eruptions and for continuous passive degassing volcanoes.Here, we present a global overview of BrO/SO2 molar ratios in volcanic dispersion gas plumes derived from a systematic long-term investigation covering four years (January 2018 to December 2021) of TROPOMI data.We retrieved column densities of BrO and SO2 using Differential Optical Absorption Spectroscopy (DOAS) and calculated mean BrO/SO2 molar ratios for various volcanoes. The calculated BrO/SO2 molar ratios differ strongly ranging from several 10-5 up to several 10-4 both between different volcanoes, but also between measurements at one volcano at different points in time. In our four-year study of S-5P/TROPOMI data we successfully recorded 4232 volcanic plumes, 3063 of which can be clearly assigned to 43 volcanoes. Subsequently, the mean BrO/SO2 ratio is calculated for these plumes - increasing the global data-base of reported BrO/SO2 ratios from 28 to 60 volcanoes. For the first time, BrO/SO2 ratios were successfully determined for six hot spot volcanoes - all of which yield low BrO/SO2 ratios between 2-5x10-5, in contrast to 2-16x10-5 for subduction zone volcanoes, suggesting a depletion of bromine in the Earth’s mantle.In addition, time-series of the BrO/SO2 ratio were derived for 19 volcanoes, with more than 200 daily measurements of the BrO/SO2 ratio at the five volcanoes Mt. Etna, Italy, Dukono, Indonesia, Popocatepetl, Mexico, Nevado del Ruiz, Colombia, and Sangay, Ecuador.

The ground-based Multiple Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurement technique is of high interest to measure local scale pollution events like trace gas plumes above cities or power plants. Besides vertical column densities and especially for the comparison with in-situ measurements and model simulations, vertical profiles of aerosol extinction and trace gas concentrations are retrieved. In this the horizontal extent of the plume is usually neglected in the forward modelling (i.e. horizontally homogeneous distribution is assumed).Here we investigate by sensitivity studies on simulated measurements 1) the systematic errors induced when in fact a horizontally limited plume is measured while neglecting the limited horizontal plume extent in the retrieval, 2) the capabilities to correct for these errors by a tomographic measurement scheme scanning the same air masses by two instruments, and 3) we provide an outlook to the practical applicability of such a measurement concept.

Halogen radicals can drastically alter the atmospheric chemistry. In the polar regions, this is made evident by the ozone depletion in the stratosphere (ozone hole) but also by destruction of boundary layer ozone during polar springs. These recurrent episodes of catalytic ozone depletion, better known as “ozone depletion events” (ODEs) are driven by enhanced concentrations of reactive bromine compounds. The proposed mechanism by which these compounds are released into the troposphere is known as “bromine explosion” - reactive bromine is formed autocatalytically from the condensed phase.In comparison to previous satellite missions, the TROPOspheric Monitoring Instrument (TROPOMI) onboard ESA’s S5-P satellite allows an improved localization and a more precise specification of these events due to its superior spatial resolution of up to 3.5 x 5.5 km2. Together with the better than daily coverage over the polar regions, this allows for investigations of the spatio-temporal variability of enhanced BrO levels and their relation to different possible bromine sources and release mechanisms.We present tropospheric BrO column densities retrieved from TROPOMI measurements using Differential Optical Absorption Spectroscopy (DOAS). One advantage of our retrieval is its independence from any external input data, thereby avoiding systematic biases from external datasets. We used a modified k-means clustering and methods from statistical data analysis to separate tropospheric and stratospheric partial columns, relying only on NO2 and O3 columns measured by the same instrument. This ensures in particular that the derived tropospheric BrO data set keeps the same high spatial resolution as the TROPOMI instrument, because no model data with coarse resolution is used. In a second step, the retrieved tropospheric slant column densities (SCDs) are converted to vertical column densities (VCDs).TROPOMI’s improved spatial resolution is then utilized to study the spatial extent and shape of BrO plumes detected in the Arctic region. For this, a combination of morphological filters and connected component labeling is used to provide a statistical overview of all enhanced BrO plumes detected above certain sensitivity thresholds in the Arctic spring of 2019. This provides a lower limit for the spatial extent of enhanced BrO events (and hence also for ODEs) of around 40-60 km. Additionally, seasonal trends in size and shape of the BrO plumes as well as correlations to relevant meteorological parameters are investigated.

A major challenge in Differential Optical Absorption Spectroscopy (DOAS) is the characterization of the light path. For the determination of the light path length, cloud conditions are essential. While instruments like a LIDAR/ceilometer provide information on cloud base height in zenith direction, it is often quite challenging to obtain information on cloud coverage in the line of sight of a Multi-Axes-DOAS (MAX-DOAS) instrument.In this study, we apply an existing cloud classification algorithm using combined information from the colour index and the O4 slant column density (Wagner et al., 2013) on spectra recorded by a MAX-DOAS instrument. In order to validate the algorithm, a MAX-DOAS with camera measurements of the sky conditions carried out at the Max Planck Institute for Chemistry in Mainz for several months. The results of the cloud classification algorithm are compared to the recordings of the cameras in order to analyse the performance of the algorithm.

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.

We present an updated (v2) catalog of NOx emissions from point sources as derived from TROPOspheric Monitoring Instrument (TROPOMI) measurements of NO2 (Products Algorithm Laboratory (PAL) product) combined with wind fields from ERA5. Compared to version 1 of the catalog (Beirle et al., 2021), several improvements have been introduced to the algorithm. Most importantly, several corrections are applied, accounting for the effects of plume height on satellite sensitivity, 3D topographic effects, and the chemical loss of NOx, resulting in considerably higher and more accurate NOx emissions. In addition, error estimates are provided for each point source, taking into account the uncertainties of the individual retrieval steps. The v2 catalog is based on a fully automated iterative detection algorithm of point sources worldwide. It lists 1139 locations that have been found to be significant NOx sources. The majority of these locations match power plants listed in the Global Power Plant Database (GPPD). Other NOx point sources correspond to cement plants, metal smelters, industrial areas, or medium-sized cities. The emissions listed in v2 of the catalog show good agreement (within 20 % on average) to emissions reported by the German Environment Agency (Umweltbundesamt, UBA) as well as the United States Environmental Protection Agency (EPA). The data are publicly available at https://doi.org/10.26050/WDCC/No_xPointEmissionsV2 (Beirle et al., 2023).

We present a WRF-Chem simulation over central Europe with a high spatial resolution of 3 km × 3 km and a focus on nitrogen dioxide (NO₂). A regional emission inventory, issued by the German Environmental Agency, with a spatial resolution of 1 km × 1 km is used. We demonstrate, that by precise temporal modulation of the emission data (use of "temporal profiles"), significant improvement in model accuracy over existing simulations is achieved. Simulated NO₂ surface concentrations are compared to measurements from a total of 275 in-situ measurement stations in Germany, where the model was able to reproduce average noontime NO₂ concentrations with a bias of +0.9 % and R = 0.76. A comparison between modelled NO₂ vertical column densities (VCDs) and satellite observations from TROPOMI (TROPOspheric Monitoring Instrument) is conducted, where crucial aspects of the observation process, such as altitude-dependent NO₂ sensitivity as well as the influence of clouds and a priori assumptions of the retrieval, are taken into account. Simulations and satellite observations are shown to agree with a model bias of −6.6 % and R = 0.84 for monthly means. Lastly, simulated NO₂ concentration profiles are compared to profiles obtained from Multiaxis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of five European ground stations using the profile retrieval algorithms from the Mexican MAX-DOAS fit (MMF) and the Mainz Profile Algorithm (MAPA). For stations within Germany, biases of −5.9 % to +50.3 % were obtained when comparing average noontime NO₂ concentrations at different altitudes. Outside of Germany, where lower resolution emission data was used, biases of up to +78.6 % were observed. Overall, the study demonstrates that temporal modulation of emission data is crucial for modelling tropospheric NO₂ realistically.

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 3-dimensional (3D) structure of volcanic plumes on the retrieval results of satellite and ground based UV-vis observations. For the analysis of such measurements usually 1D scenarios are 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 GOME-2, SCIAMACHY, or OMI, 3D effects are of minor importance, but usually these observations are not sensitive to small volcanic plumes. In contrast, observations of TROPOMI aboard 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. Especially the first two effects can lead to a strong and systematic underestimation 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 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 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 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.

We present version 1.0 of a global catalog of NOx emissions from point sources, derived from TROPOspheric Monitoring Instrument (TROPOMI) measurements of tropospheric NO2 for 2018–2019. The identification of sources and quantification of emissions are based on the divergence (spatial derivative) of the mean horizontal flux, which is highly sensitive for point sources like power plant exhaust stacks. The catalog lists 451 locations which could be clearly identified as NOx point sources by a fully automated algorithm, while ambiguous cases as well as area sources such as megacities are skipped. A total of 242 of these point sources could be automatically matched to power plants. Other NOx point sources listed in the catalog are metal smelters, cement plants, or industrial areas. The four largest localized NOx emitters are all coal combustion plants in South Africa. About 1 / 4 of all detected point sources are located in the Indian subcontinent and are mostly associated with power plants. The catalog is incomplete, mainly due to persisting gaps in the TROPOMI NO2 product at some coastlines, inaccurate or complex wind fields in coastal and mountainous regions, and high noise in the divergence maps for high background pollution. The derived emissions are generally too low, lacking a factor of about 2 up to 8 for extreme cases. This strong low bias results from combination of different effects, most of all a strong underestimation of near-surface NO2 in TROPOMI NO2 columns. Still, the catalog has high potential for checking and improving emission inventories, as it provides accurate and independent up-to-date information on the location of sources of NOx and thus also CO2 . The catalog of NOx emissions from point sources is freely available at https://doi.org/10.26050/WDCC/Quant_NOx_TROPOMI ( Beirle et al. , 2020 ) .

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.

Measurements of the atmospheric absorption of the oxygen dimer O4 are often used to characterize the atmospheric light paths, e.g. to derive properties of clouds and aerosols. Some recent studies indicated discrepancies between measurements and simulations of the atmospheric O4 absorption, while others found exact quantitative agreement. One difficulty in these studies was to correctly represent the aerosol properties in the radiative transfer simulations, e.g. due to lack of information about the vertical profiles or scattering properties.In this study we investigate MAX-DOAS measurements of the atmospheric O4 absorption during a ship cruise in April and May 2019 over the tropical Atlantic. The elevation angle of the instruments telescope is automatically stabilized in order to compensate the motion of the sea. We select measurements on one day (2 May 2019) with extremely low aerosol optical depth (between about 0.03 and 0.05 at 360 nm). For such conditions the atmospheric scattering processes are dominated by Rayleigh scattering on air molecules.Besides the MAX-DOAS measurements, also measurements by a ceilometer and sun photometer are available, which are used to constrain the atmospheric aerosol properties. The radiative transfer simulations are carried out with the full spherical radiative transfer model MCARTIM.

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.

Bromine monoxide (BrO) is a halogen radical capable of influencing atmospheric chemical processes, in particular the abundance of ozone, e. g. in the polar boundary layer and above salt lakes, in the stratosphere as well as in volcanic plumes. Furthermore, the molar bromine to sulphur ratio in volcanic gas emissions is a proxy for the magmatic composition of a volcano and potentially an eruption forecast parameter.To monitor volcanic activities on global scale, satellite measurements provide invaluable information. For these purposes, the TROPOspheric Monitoring Instrument (TROPOMI) onboard ESA’s S5-P satellite is particularly interesting: its high spatial resolution of up to 3.5x5.5km2 and daily global coverage offer great potential to detect BrO and its corresponding ratio with sulphur dioxide (BrO/SO2) even during minor eruptions and for continuous passive degassing volcanoes.Here, we present a global overview of BrO/SO2 molar ratios in volcanic plumes derived from a systematic long-term investigation covering four years (Januar 2018 to December 2021) of TROPOMI data.We retrieved column densities of BrO and SO2 using Differential Optical Absorption Spectroscopy (DOAS) and calculated mean BrO/SO2 molar ratios for various volcanoes. The calculated BrO/SO2 molar ratios differ strongly between different volcanoes, but also between measurements at one volcano at different points in time, ranging from several 10-5 up to several 10-4. In our four-year study of S5P/TROPOMI data we successfully recorded elevated BrO column densities at 506 volcanic events. We were able to derive significant BrO/SO2 ratios at 26 different volcanoes on 378 occasions, thus adding an important volcanic parameter to these volcanoes.In addition, this large data set of events allows to deduce time-series of several very active volcanoes, such as Mount Etna, Italy and Ambrym, Vanuatu.

Nitrogen oxides (NOx = NO + NO2) have a negative impact on human health and play an important role in tropospheric air chemistry. Inland waterway vessels are equipped with long lasting diesel engines that emit NOx and might have a significant impact on the local air quality. This is particularly relevant for the residential areas that are located along intensively used waterways, e.g. the Rhine River. Monitoring of NOx emissions from inland waterway vessels could provide the local authorities with valuable information about ship contribution to air pollution.In this presentation we show that ground-based MAX-DOAS (Multi AXis-Differential Optical Absorption Spectroscopy) measurements, performed at the Rhine River in western Germany, are feasible for the emission plume identification from individual inland waterway vessels. However, especially for ships with rather low emissions, not always an unambiguous detection is possible, especially if the tropospheric NO2 background is high and variable. For such cases we developed an automatic background correction, and we analysed the emissions in a more statistical way. The focus of this study is put on this method by investigating the height dependency of the averaging background-corrected NO2 signals and finally estimating average NOx emissions from inland ships.

Multi-AXis (MAX)-Differential Optical Absorption Spectroscopy (DOAS) measurements use spectra of scattered sun light recorded under different elevation angles. Such measurements allow the retrievals of tropospheric vertical column densities (VCDs) and aerosol optical depths (AODs) as well as vertical profiles of atmospheric trace gases and aerosols for the lower troposphere. Further, this kind of measurement enables the simultaneous observation of multiple trace gases, e.g. formaldehyde (HCHO), glyoxal (CHOCHO) and nitrogen dioxide (NO2), with one measurement setup. Together with international partners, we run several long-term MAX-DOAS measurements at different places around the globe and conducted intensive measurement campaigns at various locations. These campaign data sets include both stationary and mobile (car and ship MAX-DOAS) measurements. For our measurements self-built so-called Tube MAX-DOAS instruments were used which cover a wavelength range of approximately 302 to 465 nm with a FWHM of around 0.65 nm.In the presented study, we focus on measurements of tropospheric formaldehyde which is mainly secondarily produced by reactions from precursor substances. However, in small amounts it can also be emitted directly by anthropogenic and biogenic activities. Further, HCHO plays an important role in atmospheric chemistry. As secondarily produced HCHO is an intermediate product of basic oxidation cycles of other hydrocarbons (also referred to as volatile organic compounds (VOCs)) observations of HCHO can be used as an indicator for VOCs. Since our measurements were taken at different places with different underlying meteorological and environmental conditions, our large data set allows to gain insights into the contributions from different sources and chemical processes covering various geographic and environmental conditions. Here, it is important to note that compared to satellite instruments, MAX-DOAS instruments have a much higher sensitivity to boundary layer HCHO (by a factor of 10 or more).In this presentation we try to identify different pollution levels, source contributions and chemical regimes of formaldehyde by combining HCHO VCDs, surface values and profiles with the same properties of other trace species such as NO2, CHOCHO and aerosols. The results will be compared for four measurement sites, namely the stations at Mainz/Germany, Bayfordbury/United Kingdom, Mohali/India and the Amazonian Tall Tower Observatory (ATTO) measurement site/Brasil.

Halogen radicals can drastically alter the atmospheric chemistry. In the polar regions, this is made evident by the ozone depletion in the stratosphere (ozone hole) but also by localized destruction of boundary layer ozone during polar springs. These recurrent episodes of catalytic ozone depletion, better known as “ozone depletion events” (ODEs) are caused by enhanced concentrations of reactive bromine compounds. The proposed mechanism by which these compounds are released into the troposphere is called “bromine explosion” - reactive bromine is formed autocatalytically from the condensed phase.In comparison to previous satellite missions, the TROPOspheric Monitoring Instrument (TROPOMI) onboard ESA’s S5-P satellite allows for an improved localization and a more precise specification of these events due to its superior spatial resolution of up to 3.5 x 5.5 km2. Together with the better than daily coverage over the polar regions, this allows for investigations of the spatiotemporal variability of enhanced BrO levels and their relation to different possible bromine sources and release mechanisms.We present tropospheric BrO column densities retrieved from TROPOMI measurements using Differential Optical Absorption Spectroscopy (DOAS). The advantage of our retrieval is its independence from any external input data. We used a modified k-means clustering and methods from statistical data analysis to separate tropospheric and stratospheric partial columns, thereby relying only on NO2 and O3 columns measured by the same instrument. This ensures in particular that the derived tropospheric BrO data set keeps the same spatial resolution as the TROPOMI instrument, because no model data with coarse resolution is used. In a second step, the BrO slant column densities (SCDs) are converted into vertical column densities (VCDs) by using an air mass factor (AMF). These AMFs are derived using a look-up table (LUT) generated by the McArtim radiative transfer model. From this LUT the AMF is calculated for each pixel using measured O4 SCDs and reflectance data. In a last step, satellite pixels are differentiated by their sensitivity to the lower troposphere using the determined AMF. This allows the exclusion of measurements deemed not sensitive to the troposphere from the dataset and gives a high confidence in the remaining retrieved values.Our retrieval algorithm avoids systematic biases from external data sets and climatologies and is therefore particularly well suited to compare the retrieved VCDs to additional environmental parameters suspected to alter the release and distribution of BrO during Arctic spring. We examine tropospheric BrO enhancements through case studies, with particular emphasis on the interconnection of ODEs and meteorology. We focus here on the relation of tropospheric BrO to mean sea level pressure, surface air temperature, sea ice age and wind speed and direction. In addition, the spatiotemporal extent of events is studied and compared to WRF-Chem simulations.

With a nearly continuously effusive eruption since 1983, the Kilauea volcano (Hawaii, USA) is one of the most active volcanoes in the world. From the beginning of May till the end of August 2018, a sequence of eruptions on the Lower East Rift Zone (LERZ) caused an enhanced outbreak of volcanic gases and aerosols, releasing them into the troposphere. Since these gases and particles affect climate, environment, traffic, and health on regional to global scales, a continuous monitoring of the emission rates is essential.As satellites provide the opportunity to observe and quantify the emissions remotely from space, their contribution to the monitoring of volcanoes is significant. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite was successfully launched by the end of 2017 and provides measurements with unprecedented level of detail at a resolution of 3.5 x 7.0 km2 (3.5 x 5.5 km2 since August 2019). This also allows for an accurate retrieval of trace gas species such as volcanic SO2. Here, we show that the location and strength of SO2 emissions from Kilauea can be determined by the divergence of the temporal mean SO2 flux. This approach, which is based on the continuity equation, has been successfully demonstrated for NOX emissions of individual power plants (Beirle et al., Sci. Adv., 2019).The present state of our work also indicates that emission maps of SO2 can be derived by the combination of satellite measurements and wind fields on high spatial resolution. As the divergence is highly sensitive on point sources like the erupting fissures in the 2018 Kilauea eruption, they can be localized very precisely. The obtained emission rates of about 1.5 Mt are substantially lower than the ones reported from ground-based measurements in other studies like the one from Kern et al. (Bull. Volcanol., 2020). We discuss several potential reasons for the discrepancies between the ground- and satellite-based observations like e.g. uncertainties of the air mass factor or possible rapid destruction of SO2 in the presence of clouds.

Spectroscopic measurements of scattered sun light are widely used to retrieve atmospheric trace gas distributions. Usually, the used instruments are not radiometrically calibrated, because for the analysis of the narrow-band molecular absorptions no absolute calibration is needed. For some applications, however, an absolute radiance calibration is needed, e.g. for the determination of aerosol and cloud properties or actinic fluxes.The radiance calibration is usually performed in the laboratory using calibrated light sources. However, such calibrations have their own uncertainties. Moreover, during transport of the instruments from the laboratory to the field, often changes of the instrument properties occur.Here we propose a new calibration method which can be directly applied in the field using measurements of zenith scattered sun light. We found that especially during sunset and sunrise, the scattered light intensity from the zenith is rather insensitive to the effect of atmospheric aerosol scattering. If e.g. the AOD is 0.3 or less, while the actual AOD is not known, the respective uncertainties of the radiance calibrations at an SZA of 90° are about 5% at 340nm, 8% at 380nm, or 12% at 440nm. For larger wavelengths, the uncertainties increase strongly. If, however, the AOD is known within about 0.1, the corresponding uncertainties are much smaller, ranging between about 2% at 340nm and about 12% at 700nm. These uncertainties also include the effects of the uncertainties of the surface albedo, aerosol optical properties, their vertical profiles as well as variations of the stratospheric ozone absorption, the stratospheric aerosols and the effect of Raman scattering. Thus, in combination with sun photometer measurements a radiometric calibration even at larger wavelengths is feasible. It should be noted that the RTM simulations have to be performed including polarisation.We present sensitivity studies based on radiative transfer simulations, the application of the new method to real measurements and a comparison to independent measurements.

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.

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. 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 (360 nm) and we show that the agreement strongly depends on the O4 scaling factor that is used in the analysis. The trace gas differential slant column densities (dSCDs), simulated by the forward models, are also in good agreement, except for HCHO, where larger scatter is observed due to the increased spectral noise of the measurements in the UV. The agreement for NO2 and HCHO surface concentrations is similar to the comparison of the integrated columns with slightly decreased correlation coefficients. 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 and Brewer 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 the true aerosol profile is 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 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 and the Brewer.

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.

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 real O4 VCD, as derived from vertically integrated profiles, within −0.9 % ± 1.0 % for WRF simulations around Germany, 0.1 % ± 1.2 % for global reanalysis data (ERA5), and −0.4 % ± 1.4 % for 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.