The Copernicus Sentinel-4/UVN and Sentinel-5/UVNS imaging spectrometers, hosted on EUMETSAT’s Meteosat Third Generation - Sounder (MTG-S) and EUMETSAT Polar System - Second Generation A (EPS-SG A) satellites, are in space since the summer of 2025. Sentinel-4/UVN is designed to monitor atmospheric trace gases - such as ozone, nitrogen dioxide, sulphur dioxide, formaldehyde and glyoxal - as well as aerosol and cloud properties from hyperspectral measurements in the UV, Visible and Near-Infrared (UVN). Observing from a geostationary orbit, it provides high spatial resolution and hourly coverage over Europe and northern Africa. Sentinel-5/UVNS has a similar scope but additionally covers spectral bands in the Shortwave-Infrared and therefore allows measuring additional species, such as carbon monoxide and methane. Flying in a polar orbit, it provides high spatial resolution and near-daily global coverage. Both instruments provide essential data for tracking atmospheric composition and support the Copernicus Atmosphere Monitoring Service (CAMS). The innovative instruments are completing the European contribution to the constellation of geostationary and polar orbiting atmospheric composition missions, including the existing geostationary GEMS and TEMPO over Asia and North America, respectively, as well as the fleet of Low Earth Orbit air quality missions operating in similar spectral ranges, such as GOME-2, OMI, TROPOMI and OMPS. This presentation will cover the mission status during the ongoing commissioning and Cal/Val activities, including insights into level-2 product status.

Characterizing the light path through the atmosphere is a fundamental challenge in Differential Optical Absorption Spectroscopy (DOAS). Clouds strongly influence the light paths and thus the interpretation and further use of the measurements. In this context, it is important to receive information about the cloud cover in the field of view of the Multi-AXis-DOAS (MAX-DOAS) instrument. A method for extracting this information from the measured spectra themselves was introduced by Wagner et al. (2014, 2016). They developed an algorithm to determine and classify sky conditions based on the combination of CI (Colour Index) and O4 absorption obtained from MAX-DOAS spectra. In this study, the improvements of an updated version of this algorithm are presented and validated by comparison with a series of observations with camera measurements of sky conditions at several stations. In order to process the large number of observations, a tool was implemented to enable rapid categorization of the camera images.

The TROPOspheric Monitoring Instrument (TROPOMI), aboard the Sentinel-5 Precursor (S5P) satellite launched in October 2017, is dedicated to monitoring the atmospheric composition associated with air quality and climate change. This paper presents the global retrieval of TROPOMI tropospheric formaldehyde (HCHO) and nitrogen dioxide (NO2) vertical columns using an updated version of the Peking University OMI NO2 (POMINO) algorithm, which focuses on improving the calculation of air mass factors (AMFs). The algorithm features explicit corrections for the surface reflectance anisotropy and aerosol optical effects, and it uses daily high-resolution (0.25°×0.25°) a priori HCHO and NO2 profiles from the Global Earth Observing System Composition Forecast (GEOS-CF) dataset. For cloud correction, a consistent approach is used for both HCHO and NO2 retrievals, where (1) the cloud fraction is recalculated at 440 nm using the same ancillary parameters as those used in the NO2 AMF calculation, and (2) the cloud-top pressure is taken from the operational FRESCO-S cloud product. The comparison between POMINO and reprocessed (RPRO) operational products in April, July and October 2021 as well as January 2022 exhibits high spatial agreement, but RPRO tropospheric HCHO and NO2 columns are lower by 10 % to 20 % over polluted regions. Sensitivity tests with POMINO show that the HCHO retrieval differences are mainly caused by different aerosol correction methods (implicit versus explicit), prior information on vertical profile shapes and background corrections, while the NO2 retrieval discrepancies result from different aerosol corrections, surface reflectances and a priori vertical profile shapes as well as their nonlinear interactions. With explicit aerosol corrections, the HCHO structural uncertainty due to the cloud correction using different cloud parameters is within ±20 %, mainly caused by cloud height differences. Validation against ground-based measurements from global Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations and the Pandonia Global Network (PGN) shows that in April, July and October 2021 as well as in January 2022 POMINO retrievals present a comparable day-to-day correlation but a reduced bias (normalized mean bias, NMB) compared to the RPRO products (HCHO: R=0.62, NMB=-30.8% versus R=0.68, NMB=-35.0%; NO2: R=0.84, NMB=-9.5% versus R=0.85, NMB=-19.4%). An improved agreement of the HCHO/NO2 ratio (FNR, formaldehyde to nitrogen dioxide ratio) with MAX-DOAS and PGN measurements based on POMINO retrievals is also found (NMB: −14.8 % versus −21.1 %). Our POMINO retrieval provides a useful source of information, particularly for studies combining HCHO and NO2.

EUMETSAT will operate the Copernicus Sentinel-4/UVN imaging spectrometer, which is hosted on the Meteosat Third Generation - Sounder (MTG-S) satellite. The first satellite in this series is scheduled to launch in the second half of 2025.Developed by Airbus Defence and Space under an ESA contract, Sentinel-4/UVN is designed to monitor atmospheric trace gases - such as ozone, nitrogen dioxide, sulfur dioxide, formaldehyde and glyoxal - as well as aerosol and cloud properties from hyperspectral measurements in the UV, Visible and Near-Infrared (UVN). It provides high spatial resolution and hourly coverage over Europe and northern Africa, which is vital for tracking atmospheric composition and serves as a key input to the Copernicus Atmosphere Monitoring Service (CAMS). This innovative instrument will solidify the European contribution to a constellation of geostationary instruments, including the existing GEMS and TEMPO over Asia and North America, respectively. This Geo-Ring will be complemented by the fleet of Low Earth Orbit air quality missions operating in similar spectral ranges, such as GOME-2, OMI, TROPOMI, OMPS and the new Sentinel-5/UVNS mission, providing global daily coverage.This presentation will provide an overview of the Sentinel-4/UVN instrument and its products, along with the latest updates on the status of the ground segment developments. Some insight into the analysis of the instrument's calibration key data will be part of the presentation.We will also present the progress of EUMETSAT's data processing and monitoring facility, which is being prepared for commissioning and routine operations. This includes activities for the preparation of the calibration and validation (Cal/Val) of operational atmospheric chemistry products, performed centrally at EUMETSAT as well as with support from the scientific community.

Cloud properties play an important role in the evaluation and interpretation of Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements. Clouds strongly influence the length of atmospheric light paths, and are thus important for deriving the aerosol optical depth (AOD) and vertical column density (VCD) of trace gases from MAX-DOAS measurements. As such, information about the cloud properties is important to interpret the data. This study focuses on comparing three methods to derive information on cloud properties which can be run in conjunction with MAX-DOAS measurements, allowing for a more comprehensive characterisation of cloud effects: a ceilometer, an infrared camera and information derived from the MAX-DOAS measurements themselves. All instruments are located at the Max-Planck Institute for Chemistry in Mainz, Germany. We investigate, under which cloud conditions MAX-DOAS inversions might yield reasonable results and under which cloud conditions inversion results have large uncertainties. One focus of our investigation is the effect of cloud altitude on the MAX-DOAS retrievals.

The Copernicus Sentinel-4/UVN mission is Europe's contribution to the virtual constellation of air quality related sensors in geostationary orbit. It is planned to be launched in 2025 on board EUMETSAT’s Meteosat Third Generation – Sounder (MTG-S) platform and complement the Korean GEMS and American TEMPO instruments which are already in orbit over Asia and North America, respectively. Following the space segment development and in-orbit commissioning under ESA responsibility, EUMETSAT will be responsible for operations, data processing and continuous calibration/validation of the Copernicus Sentinel-4 instruments and the derived operational products. The state-of-the-art UVN sounder onboard the MTG-S satellite covers the UV to NIR spectral range to provide hourly high spatial resolution measurements of several trace gas and aerosol concentrations and vertical profiles, crucial for monitoring atmospheric pollution. Other instruments (e.g., the Infrared Sounder, Lightning Imager and Flexible Combined Imager) onboard the MTG platforms will provide complementary information about temperature, clouds, and atmospheric constituents like water vapour. In this presentation, we will cover the progress achieved at EUMETSAT for the Sentinel-4 UVN mission with respect to the readiness of the ground segment including the in-orbit calibration key data (CKD) generation. We will put forward the in-flight measurement sequences and manoeuvres that are meant to secure the quality of the generated L1 and L2 data. We will show the results of the system validation test performed with the EUMETSAT ground segment and Telespazio after the successful mechanical integration of the instrument onto the platform in September 2023. We will also present the ongoing preparation and planned activities concerning the development of tools and facilities for monitoring and operational validation.

We present WRF-Chem simulations over central Europe with a spatial resolution of 3 km × 3 km and 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 as input. We demonstrate by comparison of five different model setups that significant improvements in model accuracy can be achieved by choosing the appropriate boundary layer scheme, increasing vertical mixing strength, and/or tuning the temporal modulation of the emission data (“temporal profiles”) driving the model. The model setup with improved vertical mixing is shown to produce the best results. 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 ca. −3 % and R=0.74. The best agreement is achieved when correcting for the presumed NOy cross sensitivity of the molybdenum-based in situ measurements by computing an NOy correction factor from modelled peroxyacetyl nitrate (PAN) and nitric acid (HNO3) mixing ratios. A comparison between modelled NO2 vertical column densities (VCDs) and satellite observations from TROPOMI (TROPOspheric Monitoring Instrument) is conducted with averaging kernels taken into account. Simulations and satellite observations are shown to agree with a bias of +5.5 % and R=0.87 for monthly means. Lastly, simulated NO2 concentration profiles are compared to noontime NO2 profiles obtained from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements at five locations in Europe. For stations within Germany, average biases of −25.3 % to +12.0 % were obtained. Outside of Germany, where lower-resolution emission data were used, biases of up to +50.7 % were observed. Overall, the study demonstrates the high sensitivity of modelled NO2 to the mixing processes in the boundary layer and the diurnal distribution of emissions.

Airborne imaging differential optical absorption spectroscopy (DOAS), ground-based stationary DOAS, and car DOAS measurements were conducted during the S5P-VAL-DE-Ruhr campaign in September 2020. The campaign area is located in the Rhine-Ruhr region of North Rhine-Westphalia, western Germany, which is a pollution hotspot in Europe comprising urban and large industrial sources. The DOAS measurements are used to validate spaceborne NO2 tropospheric vertical column density (VCD) data products from the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI).Seven flights were performed with the airborne imaging DOAS instrument for measurements of atmospheric pollution (AirMAP), providing measurements that were used to create continuous maps of NO2 in the layer below the aircraft. These flights cover many S5P ground pixels within an area of 30 km x 35 km and were accompanied by ground-based stationary measurements and three mobile car DOAS instruments. Stationary measurements were conducted by two Pandora, two Zenith-DOAS, and two MAX-DOAS instruments. Ground-based stationary and car DOAS measurements are used to evaluate the AirMAP tropospheric NO2 VCDs and show high Pearson correlation coefficients of 0.88 and 0.89 and slopes of 0.90 +/- 0.09 and 0.89 +/- 0.02 for the stationary and car DOAS, respectively.Having a spatial resolution of about 100 m x 30 m, the AirMAP tropospheric NO2 VCD data create a link between the ground-based and the TROPOMI measurements with a nadir resolution of 3.5 km x 5.5 km and are therefore well suited to validate the TROPOMI tropospheric NO2 VCD. The observations on the 7 flight days show strong NO2 variability, which is dependent on the three target areas, the day of the week, and the meteorological conditions.The AirMAP campaign data set is compared to the TROPOMI NO2 operational offline (OFFL) V01.03.02 data product, the reprocessed NO2 data using the V02.03.01 of the official level-2 processor provided by the Product Algorithm Laboratory (PAL), and several scientific TROPOMI NO2 data products. The AirMAP and TROPOMI OFFL V01.03.02 data are highly correlated (r=0.87) but show an underestimation of the TROPOMI data with a slope of 0.38 +/- 0.02 and a median relative difference of -9 %. With the modifications in the NO2 retrieval implemented in the PAL V02.03.01 product, the slope and median relative difference increased to 0.83 +/- 0.06 and +20 %. However, the modifications resulted in larger scatter and the correlation decreased significantly to r=0.72. The results can be improved by not applying a cloud correction for the TROPOMI data in conditions with high aerosol load and when cloud pressures are retrieved close to the surface. The influence of spatially more highly resolved a priori NO2 vertical profiles and surface reflectivity are investigated using scientific TROPOMI tropospheric NO2 VCD data products. The comparison of the AirMAP campaign data set to the scientific data products shows that the choice of surface reflectivity database has a minor impact on the tropospheric NO2 VCD retrieval in the campaign region and season. In comparison, the replacement of the a priori NO2 profile in combination with the improvements in the retrieval of the PAL V02.03.01 product regarding cloud heights can further increase the tropospheric NO2 VCDs. This study demonstrates that the underestimation of the TROPOMI tropospheric NO2 VCD product with respect to the validation data set has been and can be further significantly improved.

We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O-3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO2) (daily products , ; monthly products , ). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products.The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public.

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.

The atmospheric oxidation of biogenic volatile organic compounds (BVOC) by OH radicals over tropical rainforests impacts local particle production and the lifetime of globally distributed chemically and radiatively active gases. For the pristine Amazon rainforest during the dry season, we empirically determined the diurnal OH radical variability at the forest-atmosphere interface region between 80 and 325 m from 07:00 to 15:00 LT using BVOC measurements. A dynamic time warping approach was applied showing that median averaged mixing times between 80 to 325 m decrease from 105 to 15 min over this time period. The inferred OH concentrations show evidence for an early morning OH peak (07:00–08:00 LT) and an OH maximum (14:00 LT) reaching 2.2 (0.2, 3.8) × 10 6 molecules cm −3 controlled by the coupling between BVOC emission fluxes, nocturnal NO x accumulation, convective turbulence, air chemistry and photolysis rates. The results were evaluated with a turbulence resolving transport (DALES), a regional scale (WRF-Chem) and a global (EMAC) atmospheric chemistry model.

<p>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.</p> <p>In this study, we apply an existing cloud classification algorithm using combined information from the colour index and the O<sub>4</sub> 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.</p>

Organ donation is remarkable achievement in modern medicine which helps those suffering from chronic incurable end organ diseases. However, the process of organ donation and transplantation is not devoid of ground level difficulties like timely diagnosis of brain death, harvesting of organs during the supravital period, transporting the retrieved organ to a facility where transplantation is to be conducted and in Medicolegal cases the Forensic Pathologist has to examine the patient and allow/disallow the retrieval of organ based on their necessity in determining cause of death. The Forensic Pathologists can do their bit in expediting the above mentioned process by conducting the autopsy in operation theatre where organs were retrieved. This practice is being followed in Telangana, Tamil Nadu and now in Karnataka. This paper aims to study the profile of organ donors, analyze the types of organs retrieved and to highlight the role of Forensic Pathologistsin expediting the process of organ donation and transplantation.

Abstract. 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.

Nitrogen oxides (NOx) are among the six criteria air pollutants that have detrimental effects on both individual and ecosystem level. The rapid industrial development over the last three decades has caused worsening in air quality through the increase in ambient levels of air pollutants including NOx. Considerable development has been made in the last decade regarding the measurement of NOx in India both using ground-based and space-borne sensors. These measurements have enabled the identification of trends and seasonality, identification of emissions sources, and understanding of chemistry and dynamics governing the ambient levels of NOx. This chapter provides an overview of NOx measurements in India and the inference drawn from these studies.

This paper discusses the comparative results of surface and satellite measurements made during the Phase1 (25 March to 14 April), Phase2 (15 April to 3 May) and Phase3 (3 May to 17May) of Covid-19 imposed lockdown periods of 2020 and those of the same locations and periods during 2019 over India. These comparative analyses are performed for Indian states and Tier 1 megacities where economic activities have been severely affected with the nationwide lockdown. The focus is on changes in the surface concentration of sulfur dioxide (SO2), carbon monoxide (CO), PM2.5 and PM10, Ozone (O3), Nitrogen dioxide (NO2) and retrieved columnar NO2 from TROPOMI and Aerosol Optical Depth (AOD) from MODIS satellite. Surface concentrations of PM2.5 were reduced by 30.59%, 31.64% and 37.06%, PM10 by 40.64%, 44.95% and 46.58%, SO2 by 16.73%, 12.13% and 6.71%, columnar NO2 by 46.34%, 45.82% and 39.58% and CO by 45.08%, 41.51% and 60.45% during lockdown periods of Phase1, Phase2 and Phase3 respectively as compared to those of 2019 periods over India. During 1st phase of lockdown, model simulated PM2.5 shows overestimations to those of observed PM2.5 mass concentrations. The model underestimates the PM2.5 to those of without reduction before lockdown and 1st phase of lockdown periods. The reduction in emissions of PM2.5, PM10, CO and columnar NO2 are discussed with the surface transportation mobility maps during the study periods. Reduction in the emissions based on the observed reduction in the surface mobility data, the model showed excellent skills in capturing the observed PM2.5 concentrations. Nevertheless, during the 1st & 3rd phases of lockdown periods AOD reduced by 5 to 40%. Surface O3 was increased by 1.52% and 5.91% during 1st and 3rd Phases of lockdown periods respectively, while decreased by -8.29% during 2nd Phase of lockdown period.

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.

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.

Most of the published articles which document changes in atmospheric compositions during the various lockdown and unlock phases of COVID-19 pandemic have made a direct comparison to a reference point (which may be 1 year apart) for attribution of the COVID-mediated lockdown impact on atmospheric composition. In the present study, we offer a better attribution of the lockdown impacts by also considering the effect of meteorology and seasonality. We decrease the temporal distance between the impacted and reference points by considering the difference of adjacent periods first and then comparing the impacted point to the mean of several reference points in the previous years. Additionally, we conduct a multi-station analysis to get a holistic effect of the different climatic and emission regimes. In several places in eastern and coastal India, the seasonally induced changes already pointed to a decrease in PM concentrations based on the previous year data; hence, the actual decrease due to lockdown would be much less than that observed just on the basis of difference of concentrations between subsequent periods. In contrast, northern Indian stations would normally show an increase in PM concentration at the time of the year when lockdown was effected; hence, actual lockdown-induced change would be in surplus of the observed change. The impact of wind-borne transport of pollutants to the study sites dominates over the dilution effects. Box model simulations point to a VOC-sensitive composition.

An updated and expanded representation of organics in the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) has been evaluated. First, the comprehensive Mainz Organic Mechanism (MOM) in the submodel MECCA (Module Efficiently Calculating the Chemistry of the Atmosphere) was activated with explicit degradation of organic species up to five carbon atoms and a simplified mechanism for larger molecules. Second, the ORACLE submodel (version 1.0) now considers condensation on aerosols for all organics in the mechanism. Parameterizations for aerosol yields are used only for the lumped species that are not included in the explicit mechanism. The simultaneous usage of MOM and ORACLE allows an efficient estimation of not only the chemical degradation of the simulated volatile organic compounds but also the contribution of organics to the growth and fate of (organic) aerosol, with the complexity of the mechanism largely increased compared to EMAC simulations with more simplified chemistry. The model evaluation presented here reveals that the OH concentration is reproduced well globally, whereas significant biases for observed oxygenated organics are present. We also investigate the general properties of the aerosols and their composition, showing that the more sophisticated and process-oriented secondary aerosol formation does not degrade the good agreement of previous model configurations with observations at the surface, allowing further research in the field of gas–aerosol interactions.