AS3.30 | Satellite observations of tropospheric composition and pollution, analyses with models and applications
Satellite observations of tropospheric composition and pollution, analyses with models and applications
Convener: Andreas Richter | Co-conveners: Cathy Clerbaux, Pieternel Levelt, Camille ViatteECSECS
| Wed, 17 Apr, 14:00–17:55 (CEST)
Room M1
Posters on site
| Attendance Thu, 18 Apr, 10:45–12:30 (CEST) | Display Thu, 18 Apr, 08:30–12:30
Hall X5
Orals |
Wed, 14:00
Thu, 10:45
Over the last years, more and more satellite data on tropospheric
composition have become available and are now being used in numerous
applications. In this session, we aim at bringing together reports on
new or improved data products and their validation as well as studies
using satellite data for applications in tropospheric chemistry,
emission inversions and air quality. This includes both studies on trace
gases and on aerosols.

We welcome presentations based on studies analysing current and future
satellite missions, in particular Sentinel 5P and GEMS,
inter-comparisons of different remote sensing measurements dedicated to
tropospheric chemistry sounding and/or analyses with ground-based
measurements and chemical transport models.

Orals: Wed, 17 Apr | Room M1

Chairpersons: Andreas Richter, Camille Viatte
On-site presentation
Naveed Ahmad, Changqing Lin, Alexis K.H. Lau, Jhoon Kim, Kai Qin, Chengcai Li, and Jimmy C.H. Fung

Ozone (O3) and nitrogen dioxide (NO2) are critical atmospheric trace gases due to their role in air quality, oxidative chemistry, and climate forcing. Both O3 and NO2 were formerly monitored from space on a daily basis using sun-synchronous polar orbiting satellite instruments. However, the Geostationary Environment Monitoring Spectrometer (GEMS) now provides hourly measurements during the daylight hours over East Asia. Since GEMS is a newly launched satellite instrument, to check the accuracy and uncertainties associated with the first version of its dataset, there is a need for its evaluation through ground-based instruments over the Chinese region. This study presents the systematic evaluation of GEMS hourly measurements of Column Amount NO2 (NO2 VCDs) and Ozone Profile (O3P) by using ground-based measurements. The MAX-DOAS measurements were conducted in Xuzhou in eastern China for one week of each of the four seasons in 2021 to have a better representation of both high and low NO2 concentrations. NO2 variations were well captured in all seasons by both instruments, with higher VCDs in winter and lower during the summer.  A good correlation (R = 0.82) between MAX-DOAS and GEMS was found. However, GEMS underestimated the NO2 VCDs with a consolidated mean deviation (without seasonal discrimination) by -1.87 ± 8.73 x 1015 molec/cm2. The comparison of hourly GEMS NO2 VCDs with in-situ measurements available across China for 2021 has shown a good correlation coefficient of around 0.4-0.6 and higher, particularly in the highly polluted region of the North China Plain. Then, to evaluate the GEMS ozone profile, we used Ozonesonde measurements available for 2021 in Hong Kong, situated in the southern part of China. For the vertical profile of ozone in the troposphere and lower stratosphere, GEMS and Ozonsonde depicted a similar pattern. However, in the troposphere, the Ozonesonde measurements were slightly underestimated, while in the stratosphere, GEMS showed underestimation. It is pertinent to mention that both instruments depicted peak ozone concentrations at an altitude of around 24 to 27 km. The correlation between the two instruments was good, particularly in the lower troposphere (R = 0.74) at 4 km. Further, the lowest layer of the GEMS ozone profile was compared with in-situ measurements for 2021 across the entire Chinese region, and a good correlation coefficient (R: 0.4 - 0.6) was observed. These findings are meaningful scientific advancement enhancing our understanding of the potential of the first geostationary satellite instrument to monitor atmospheric trace gases (O3 and NO2) hourly. More robust validations are recommended in other regions to understand the uncertainties associated with the local conditions and to further improve the GEMS products in future versions of datasets.

How to cite: Ahmad, N., Lin, C., K.H. Lau, A., Kim, J., Qin, K., Li, C., and C.H. Fung, J.: Evaluation of Ozone Profile and NO2 vertical column densities of Geostationary Environment Monitoring Spectrometer (GEMS) in China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-208,, 2024.

On-site presentation
Vitali Fioletov, Chris McLinden, Debora Griffin, Xiaoyi Zhao, and Henk Eskes

The tropospheric NO2 vertical column density (VCD) values measured by the Tropospheric Monitoring Instrument (TROPOMI) were used to study the NO2 variability and estimate urban NO2 emissions for 261 major cities worldwide. The used algorithm isolated three components in tropospheric NO2 data: background NO2, NO2 from urban sources, and from industrial point sources, and then each of these components was analyzed separately. The method is based on fitting satellite data by a statistical model with empirical plume dispersion functions driven by a meteorological reanalysis. Unlike other similar studies that studied plumes from emission point sources, this study included the background component as a function of the elevation in the analysis and separated urban emissions from emissions from industrial point sources. Population density and surface elevation data as well as coordinates of industrial sources were used in the analysis. Differences between workday and weekend emissions were also studied. Urban emissions on Sundays (or Fridays for some countries) are typically 20%-50% less than workday emissions for all regions except China. No significant difference in urban emissions between seasons was found. In contrast, the background component does not show any significant differences between workdays and weekends suggesting that background NO2 has a substantially longer lifetime compared to that in the plumes. 

How to cite: Fioletov, V., McLinden, C., Griffin, D., Zhao, X., and Eskes, H.: Quantifying seasonal urban NO2 emissions using satellite observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2156,, 2024.

On-site presentation
Eloise Marais, Gongda Lu, Karn Vohra, Rebekah Horner, Dandan Zhang, Randall Martin, and Sarath Guttikunda

Cities in South and Southeast Asia are developing rapidly, but lack routine, up-to-date, publicly available inventories of air pollutant precursor emissions such as nitrogen oxides (NOx). This data deficiency can be addressed by deriving city NOx emissions from satellite observations of nitrogen dioxide (NO2) tropospheric column densities. In this approach, the city plume is aligned along a consistent direction using wind rotation and a best-fit Gaussian applied to estimate NOx emissions. Issues that impact success of this approach is subjective selection of the sampling area around the city centre and the Gaussian fit often fails or yields physically implausible parameters. Here, we automate this top-down approach by defining many (54) sampling areas that we test with TROPOspheric Monitoring Instrument (TROPOMI) NO2 observations over 19 cities in South and Southeast Asia. Our approach is efficient, adaptable to a wide range of city sizes, eliminates the need for subjective sampling area selection, and increases success of deriving annual emissions from 40-60% with a single sampling area to 100% (all 19 cities) with 54 sampling areas. Annual emissions range from 16±5 mol s-1 for Yangon (Myanmar) to 118±39 mol s-1 for Dhaka (Bangladesh). A widely used global emissions inventory exhibits large (2-fold) discrepancies for 5 of the 19 cities. The increase in success achieved with our updated approach also enables derivation of monthly emissions, although all 12 months are only obtained for one city (Karachi in Pakistan). Seasonality in the monthly emissions matches seasonality in tropospheric column abundances of NO2 and is greater than can be reasoned with seasonality in anthropogenic activity in cities. This suggests that past annual emissions calculated using observations for a portion of the year or select days may be biased. Further refinement of this approach is needed to fully exploit the large sampling density of high-resolution low-Earth orbiting instruments such as TROPOMI and hourly measurements from geostationary instruments such as Geostationary Environmental Monitoring Spectrometer (GEMS), Tropospheric Emissions: Monitoring of Pollution (TEMPO), and Sentinel-4.

How to cite: Marais, E., Lu, G., Vohra, K., Horner, R., Zhang, D., Martin, R., and Guttikunda, S.: Near-Automated Estimate of City Nitrogen Oxides Emissions Applied to South and Southeast Asia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2882,, 2024.

On-site presentation
Leon Kuhn, Steffen Beirle, and Thomas Wagner

Nitrogen dioxide (NO2) is an important air pollutant and has been widely recognized for its hazardous impact on human health. Tropospheric NO2 is routinely monitored using satellites (e.g. TROPOMI onboard Sentinel-5P), in situ instruments, and ground-based spectroscopic measurements (e.g. multi-axis differential optical absorption spectroscopy, MAX-DOAS). However, these measurements do not give the full picture: Satellite instruments can only measure the integrated load (column density), in situ measurements are mostly deployed at the surface, and MAX-DOAS instruments are still very sparse. In consequence, it is currently impossible to obtain sufficiently resolved NO2 profiles from measurements alone. Regional chemistry and transport (RCT) simulations can be used to simulate NO2 profiles where no observations are available, but they are computationally expensive and require meticulous parameter calibration to achieve acceptable agreement with observational reference data.

We present NitroNet, a new deep-learning model for the prediction of tropospheric NO2 profiles. The model is based on a feedforward neural network, which was trained on a synthetic dataset from the RCT model WRF-Chem. NitroNet receives vertical NO2 column densities (VCDs) from TROPOMI and ancillary variables (meteorological, emissions, etc.) as input, from which it predicts tropospheric NO2 concentration profiles. The NO2 VCD is descriptive of the profiles' magnitudes, while their shapes are derived from the ancillaries (e.g. the boundary layer height). The ancillaries are taken from the TROPOMI NO2 data product, ERA5 reanalysis data, and the EDGARv5 emission inventory. By prior filtering of the training data based on their agreement to reference data, NitroNet can achieve better agreement with TROPOMI’s NO2 VCDs and surface in situ measurements than WRF-Chem at a much faster runtime. On the downside, these predictions are available only once per day, when the TROPOMI overpass occurs. We showcase the model’s performance against a variety of validation data (satellite, in situ, and MAX-DOAS measurements), and its ability to generalize to different seasons and geographical regions.

What makes NitroNet unique in the field of deep-learning air pollution models is its training on synthetic data. This conceptual difference to the many recently developed models, trained on empirical observations alone, unlocks important new possibilities: Due to the paucity of other observations, empirical training sets are practically confined to surface concentrations from in situ measurements. Synthetic data generation, on the other hand, allows for training sets with full NO2 profiles instead. Moreover, synthetic training examples do not suffer from the cross-sensitivities of in situ measurements to other nitrogen compounds (up to a factor of 2).

The NO2 profiles produced by NitroNet can be used as high-resolution replacements for the a priori profiles in satellite retrievals, or for studies on surface level air pollution.

How to cite: Kuhn, L., Beirle, S., and Wagner, T.: NitroNet – A new deep-learning model for the prediction of NO2 profiles based on TROPOMI satellite observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3660,, 2024.

On-site presentation
Christoph Rieß, Jasper van Vliet, and Folkert Boersma

Maritime transportation is a substantial contributor to anthropogenic NOx emissions and coastal air pollution. Recognizing this, the International Maritime Organization (IMO) has implemented stricter emission standards for NOx and SO2 in recent years. However, monitoring emissions of sea-bound vessels possesses inherent challenges, prompting the exploration of satellite observations as a promising solution. This study presents a first-ever satellite-based NOx emission inversions for multiple individual ships based on TROPOMI-observed NO2 plumes and AIS data over the Mediterranean Sea in 2019. Our inversion approach accounts for the complex, high-resolution atmospheric dynamics and chemistry that drive the relationship between the NOx emissions and observable NO2 plume. Additionally, we test how an updated Air Mass Factor (AMF) scheme – using high-resolution local plume NO2 profiles from  PARANOX simulations – improves the inversion. For the inversion, we create a large library of pseudo-observations of NO2 plumes with the Gaussian Plume Model PARANOX and test these with the large eddy simulation model MicroHH, which was run with an atmospheric chemistry scheme. The plume dispersion of the two models shows good agreement and the simulated in-plume NO2 differs by only 6%, making PARANOX a suitable (and computational efficient) model choice, especially when considering the large uncertainties related to satellite retrievals above sea.

The PARANOX library shows that background ozone and the effective wind speed determine the relationship between the ship NOx emission strength and the observable NO2 plume: Ozone drives the partitioning of the emitted NOx between NO and (observable) NO2 and the wind speed dictates the mixing and therefore lifetime of NOx in the plume. This explains the frequent occurrence of detectable ship NO2 plumes in the Eastern Mediterranean in summer, when background ozone is high and wind speeds are moderate. We study 130 NO2 plumes of individual ships found in TROPOMI data over the Mediterranean Sea in 2019, most of which are from container ships. In the early afternoon, the observed ships in the Mediterranean Sea emit on average 76g NO2 /s but reaching up to 240 g/s. Finally, these fluxes are compared against both the current IMO emission limits and the requirements for a future Emission Control Area in the Mediterranean Sea.

How to cite: Rieß, C., van Vliet, J., and Boersma, F.: TROPOMI-based NOx emission estimates of individual ships, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16869,, 2024.

On-site presentation
Cheng Liu, Xiaohan Wang, Jingkai Xue, Qihou Hu, Qihua Li, Wenjing Su, and Chengxin Zhang

Recently, China launched a series of the Environmental Trace Gases Monitoring Instruments (EMI) on satellites with different over-pass times to support global daily multi-temporal atmospheric monitoring. Compared with previous satellites in sun-synchronous orbit, such as OMI and TROPOMI which over passes at 13:30 LT, the series of Chinese EMI satellite instruments with similar performance can be used to investigate the diurnal variations in trace gases. Besides, the series of EMI expanded the areas with diurnal observation in trace gases from the North America, East Asia, and Europe, where are covered by geostationary satellite observations, to the global scales, particularly the South Hemisphere. However, how to eliminate the systematic bias between retrieval results from multiple satellites is the major difficulty.

Here we are performed further spectral calibration and inversion algorithm improvement. We use meteorological parameters and a priori atmospheric profiles at different moments in the radiative transfer calculations and inversion. Results from the Tracer Model (version 5, TM5) were also used for background correction. We use secondary radiometric calibrations, i.e. soft calibrations, to further correct the systematic biases between observed spectra from different instruments. Through these algorithm updates, we have successfully retrieved the concentrations of several trace gases, such as Ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and formaldehyde (HCHO), at different times of day (10:30 and 13:00 LT). The retrieved trace gas concentrations from the series of EMI were further used to investigate the diurnal variation in air pollutant emissions and ozone formation.

Moreover, due to the influence of factors such as cloud cover, satellite observations often have gaps. Here we used artificial intelligence (AI) analysis, such as neural operator methods, to achieve spatial full coverage of remote sensing results. We masked existing satellite observation data, and then used artificial intelligence models to repair and fill in missing areas, with ERA5 meteorological field data, various emission inventories, and geographical information data. The combination with AI analysis improved the usability and application scope of satellite data.

How to cite: Liu, C., Wang, X., Xue, J., Hu, Q., Li, Q., Su, W., and Zhang, C.: Remote sensing of trace gases from multiple Chinese satellite instruments and its application combined with AI , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4220,, 2024.

On-site presentation
Jiaqi Chen, Zhe Jiang, Kazuyuki Miyazaki, and Dylan Jones

Recent studies demonstrated the difficulties to explain observed tropospheric nitrogen dioxide (NO2) variabilities over the United States and Europe, but thorough analysis for the impacts on tropospheric NO2 in China is still lacking. Here we provide a comparative analysis for the observed and modeled (Goddard Earth Observing System-Chem) tropospheric NO2 in early 2020 in China. Both ozone monitoring instrument and surface NO2 measurements show marked decreases in NO2 abundances due to the 2019 novel coronavirus (COVID-19) controls. However, we find a large discrepancy between observed and modeled NO2 changes over highly polluted provinces: the observed reductions in tropospheric NO2 columns are about 40% lower than those in surface NO2 concentrations. By contrast, the modeled reductions in tropospheric NO2 columns are about two times higher than those in surface NO2 concentrations. This discrepancy could be driven by the combined effects from uncertainties in simulations and observations, associated with possible inaccurate simulations of lower tropospheric NO2, larger uncertainties in the modeled interannual variabilities of NO2 columns, as well as insufficient consideration of aerosol effects and a priori NO2 variability in satellite retrievals. In addition, our analysis suggests a small influence from free tropospheric NO2 backgrounds in E. China in winter. This work demonstrates the challenge to interpret wintertime tropospheric NO2 changes in China, highlighting the importance of integrating surface NO2 observations to provide better analysis for NO2 variabilities.

How to cite: Chen, J., Jiang, Z., Miyazaki, K., and Jones, D.: Large discrepancy between observed and modeled wintertimetropospheric NO2 variabilities due to COVID-19 controls in China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7013,, 2024.

On-site presentation
Nana Wei, Eloise A. Marais, and Gongda Lu

Surface concentrations of nitrogen oxides (NOx) are increasing at rates of up 10% per year in cities in Africa, as inferred with trends in long-term satellite observations of tropospheric columns of nitrogen dioxide (NO2). This is being driven by rapid population growth and urbanization in the absence of air quality policies. Models needed to inform air quality policies use out-of-date inventories for cities in Africa due to absence of detailed temporal and spatial information about emission and activity factors of sources unique to African cities. Here we apply a recently improved method of deriving city NOx emissions from satellite observations of NO2 that builds on the well-established rotation of each city NO2 plume along a consistent direction and selecting a single sampling area around the city centre to fit a modified Gaussian to calculate emissions. The improved method uses a more efficient fit routine and multiple sampling areas to eliminate subjective area selection and increase the success of deriving annual emissions from ~50% to 100%. Such an approach is ideal for African cities that have wide-ranging sizes due to the different development stages of countries and urban centres in Africa. Work is underway to quantify NOx emissions for more cities in Africa than has been achieved with global studies using 2019 observations of NO2 from the TROPOspheric Monitoring Instrument (TROPOMI). The resultant NOx emissions will then be compared to emissions estimates from widely used global (EDGAR, CEDS, HTAP) and regional (DACCIWA, DICE-Africa) inventories to assess shortcomings in inventories and the influence of these on designing evidence-based air quality policies and regulations.

How to cite: Wei, N., Marais, E. A., and Lu, G.: Deriving NOx emissions of cities in Africa using the space-based TROPOMI instrument, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10955,, 2024.

On-site presentation
Emma Sands, Richard Pope, Ruth Doherty, Fiona O'Connor, Chris Wilson, and Hugh Pumphrey

We exploit satellite datasets of spatio-temporal distributions of atmospheric composition for the rainforest and savanna region on the southern boundary of the Amazon to understand how its emissions of biogenic volatile organic compounds (BVOCs) and local pyrogenic emissions impact the atmosphere. In particular, we explore the relationship between land cover change, considering vegetation type (e.g. broadleaf forest, savanna, grassland) and Leaf Area Index (LAI), and burned area and atmospheric composition. In this study, we investigate these relationships over the southern Amazon for the period 2001-2019, focussing on seasonal and spatial patterns. We utilise data for five chemical species: total column isoprene (TCC5H8), total column methanol (TCCH3OH), tropospheric column nitrogen dioxide (TCNO2), total column carbon monoxide (TCCO) and total column formaldehyde (TCHCHO), as well as aerosol optical depth (AOD).

We find burned area approximately delineates the areas of change in dominant vegetation cover type over time.  Robust relationships were found between TCC5H8 and forest cover, and TCNO­2­ and burned area. Here, we find that TCC5H8 linearly increases by 1 × 1014 molecules cm-2 with an increase of 1 percentage point in broadleaf forest cover. This is equivalent to densely forested regions having column isoprene ­­values four times greater than those with no­ forest cover. There is a strong power law relationship between TCNO2 and burned area. Overall, there is a larger increase in TCNO2 in regions of lower, though still substantial, biomass burning (i.e. potentially new regions of burning/deforestation). These relationships highlight the relatively short lifetimes of the two species such that their spatial extent is largely confined to their emission source regions.

Conversely, TCHCHO, TCCO and AOD reach maximum values for high broadleaf forest coverage and high burned areas, suggesting a mixed influence of both biogenic and pyrogenic sources, likely due to the longer lifetimes of these species and aerosols, allowing them to mix and be transported further from their emissions sources. Broadleaf forest cover and burned area do not appear to have a substantial impact on methanol, which is elevated over a region of savanna and grasslands in the northeast of the study region.

The results highlight the potential for air quality impacts from the biogenic and pyrogenic emissions and their interactions that differ seasonally and regionally, and illustrates how land cover and land use change exerts a strong control on isoprene and nitrogen dioxide concentrations over remote regions.

How to cite: Sands, E., Pope, R., Doherty, R., O'Connor, F., Wilson, C., and Pumphrey, H.: Using satellite observations to examine the role of land cover and fires in driving atmospheric composition over the southern Amazon, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8299,, 2024.

On-site presentation
Thomas Wagner, Steffen Beirle, and Christian Borger

The Environmental Mapping and Analysis Program (EnMAP) satellite is a hyperspectral satellite instrument for the monitoring of terrestrial and aquatic ecosystems. It provides high spatial resolution (30 x 30 m²) but relatively low spectral resolution (~6.5 nm FWHM in the visible to near-infrared spectral range and ~10 nm FWHM in the shortwave IR spectral range). Although the spectral information of ENMAP observations is limited, it is possible to analyse the atmospheric NO2 and CO2 contents from ENMAP spectra for strong emission plumes using differential optical absorption spectroscopy. While the CO2 signal is close to the detection limit, the evolution of the downward NO2 plumes from power plants can be well quantified.

We present the spectral analyses of both trace gases and show measurement results for power plant plumes from Riyadh in Saudi Arabia and the Highveld in South Africa. We compare the ENMAP NO2 results to observations from the TROPOMI satellite instrument and aircraft measurements. Our results show that ENMAP NO2 and CO2 measurements can be used to study the chemical and dynamical evolution of power plant plumes. For example, the conversion of NO to NO2 can be quantified, or turbulence elements of the plumes can be clearly identified. The simultaneous observation of NO2 and CO2 might also allow the characterization of different power plants by their emission ratio. Due to the high spatial resolution of ENMAP also plumes from nearby power plants with distances of only a few hundred meters can be separated. 

How to cite: Wagner, T., Beirle, S., and Borger, C.: High-resolution satellite measurements of NO2 and CO2 in power plant plumes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9121,, 2024.

Coffee break
Chairpersons: Cathy Clerbaux, Pieternel Levelt
On-site presentation
Jhoon Kim and the GEMS Science Team

A new era of air quality observations from geostationary Earth orbit(GEO) has begun with the launch of Geostationary Environment Monitoring Spectrometer (GEMS) over Asia and Tropospheric Emission of Pollutants (TEMPO) over North America as the two components of geostationary air quality (AQ) constellation. GEMS has provided hourly observations of AQ over Asia from a GEO since November 2020. Column amounts of atmospheric pollutants (O3, NO2, SO2, HCHO, CHOCHO, and aerosols) have been provided to capture their diurnal variations with the UV–visible spectrometer at 0.6 nm spectral resolution and sophisticated retrieval algorithms. Details of the latest GEMS version 3 products are presented, including validations, calibration, and case studies of volcanic eruption, dusts, and urban pollution. In version 3, there are noticeable improvements in trace gases from updated AMF, the separation of stratospheric/tropospheric components, fitting window, spectroscopy etc. Calibration/validation activities including the ASIA-AQ, Pandora Asia network (PAN), PEGASOS, GMAP/SIJAQ, ACCLIP, and international CAL/VAL team works are critical to evaluate and improve the overall data quality. The GEMS retrievals indicate good agreements from the campaigns, but still require further improvements in L1 processing as well. We are improving L1 processor including BTDF correction. Faster sampling rates at higher spatial resolution increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than have been possible from LEO. Planned ESA’s Sentinel-4 in 2025 will complete the GEO AQ satellite constellation with GEMS and TEMPO, as recognized by the Committee on Earth Observation Satellites (CEOS).

How to cite: Kim, J. and the GEMS Science Team: Revealing Diurnal Variations of Air Quality Observations in Asia from Geostationary Environment Monitoring Spectrometer (GEMS), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8024,, 2024.

On-site presentation
Enrico Dammers and the FTIR-NH3 and satellite NH3 product teams

Ammonia (NH3) is an essential form of reactive nitrogen whose emissions originate primarily from manure and fertilizer. Atmospheric ammonia is a major precursor of anthropogenic aerosols, for example ammonium nitrate, and negatively impacts both human and ecosystem health. While important, the overall budget of ammonia remains highly uncertain, as in-situ measurements of ammonia are still sparse and typically only provide a very coarse spatial-temporal coverage. Satellite ammonia observations provide a tool to study the budget in detail, however NH3 satellite products validation studies are challenging due to the small scale spatiotemporal variability of atmospheric ammonia. Furthermore, the validation studies typically only focus on a single satellite product and/or comparison to in-situ surface concentrations. This limits such studies to more of an evaluation on how well a satellite represents a surface point measurement instead of validating the satellite vertical sounding (e.g. profile and total column) observations. The ground-based Fourier Transform infrared (FTIR)-NH3 product is an excellent dataset that can more directly evaluate the satellite column and profile type products as it shares a similar sounding measurement. Here we present an update to the FTIR-NH3 record, which includes an extension in both the number of sites as well as the observation period of these stations. Furthermore, we present the latest evaluation and intercomparison results for the most current CrIS (1, and 2), IASI(-A, -B and -C), AIRS and GOSAT(1) ammonia products.

How to cite: Dammers, E. and the FTIR-NH3 and satellite NH3 product teams: Validation of the CrIS, IASI, AIRS and GOSAT-NH3 products , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9164,, 2024.

On-site presentation
Gijs Leguijt, Joannes D. Maasakkers, Hugo A.C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, and Ilse Aben

Carbon monoxide (CO) is an air pollutant that plays an important role in atmospheric chemistry and its emissions can serve as a proxy for CO2emissions. Within the European Union, large industrial emitters are required to report their annual facility-level emissions to the European Pollutant Release and Transfer Register (E-PRTR) based on stack measurements or calculations. We use TROPOMI satellite observations of carbon monoxide concentrations to estimate the emissions and compare these to the E-PRTR reports. Since 2018, the TROPOMI satellite instrument observes carbon monoxide concentrations at a resolution down to 5.5x7 km2with daily global coverage. CO plumes from large iron and steel plants are clearly visible in the TROPOMI data, enabling us to estimate the plants’ annual emissions. To achieve this, we perform high-resolution atmospheric transport simulations with the WRF model for 2019 over the 21 highest emitting iron and steel plants in Europe. We combine the simulations with TROPOMI observed concentrations in an analytical inversion to estimate the annual emission rates of the individual plants using the E-PRTR emissions as prior estimates. The TROPOMI-based emission estimates generally agree well with the reported emission rates (R2 = 0.87) while showing limited sensitivity to the prior emission estimate. For 10 out of 21 plants the reported and TROPOMI-estimated emission rates agree within 20% whereas 6 plants show discrepancies over 40%. For the plants with the largest emissions, we perform an additional emission quantification using the Cross-Sectional Flux (CSF) method, which does not use any prior knowledge. These CSF estimates are consistent with the inversions, providing additional confidence in the space-based emission estimates. For two plants for which the 2019 inversion-based emission estimates are significantly different from the reported emission rates, we extend our analysis to 2020. The inversion estimates for 2020 agree with those from 2019 and match with reported emissions for 2020, raising questions on reported emissions for 2019. Our work shows that we can use the TROPOMI observations to reliably estimate CO emissions from large iron and steel plants and how these analyses can be used to identify uncertainties in reported emissions.

How to cite: Leguijt, G., Maasakkers, J. D., Denier van der Gon, H. A. C., Segers, A. J., Borsdorff, T., and Aben, I.: Comparing space-based to reported carbon monoxide emission estimates for Europe’s iron and steel plants., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10779,, 2024.

On-site presentation
Pramod Kumar, Philippe Ciais, Didier Hauglustaine, Gregoire Broquet, Lieven Clarisse, Martin Van Damme, and Pierre Coheur

Atmospheric ammonia (NH3) has significant environmental impacts, contributing to biodiversity loss and air quality deterioration, with potential negative effects on ecosystems and human health. The global and regional NH3 emissions have been on continuous rise in the recent years, due to the extensive use of fertilizers in agricultural activities and to livestock production. However, the current bottom-up NH3 emission inventories exhibit large uncertainties at all the spatiotemporal scales. Top-down estimates of the global and regional NH3 emissions from the atmospheric inversion approach based on satellite observations with global coverage can provide valuable insights on the spatiotemporal variability of ammonia emissions. In this study, we provide top-down atmospheric inversion estimates of the worldwide anthropogenic NH3 emissions using the new version 4 of the IASI ANNI NH3 observations for a period of four years from 2019 to 2022 at 1.27°×2.5° (latitude × longitude) horizontal resolution and at daily (as a 10-day running average) temporal scale. We use a global chemistry transport model LMDZ-INCA for the NH3 concentrations simulations and a finite difference mass balance approach for the inversions of the NH3 emissions. We take advantage of the vertical averaging kernels provided in version 4 of the IASI NH3 data product by applying them consistently to the LMDZ-INCA NH3 simulations when evaluating these simulations. We perform the global inversions to estimate the anthropogenic NH3 emissions, using the IASI NH3 total columns observations and LMDZ-INCA NH3 total columns convolved with the vertical averaging kernel. The global annual anthropogenic NH3 emissions averaged over the four years period (2019-2022) are estimated as ~90 (88-92) Tg yr-1. These global estimates are ~70% higher than the prior CEDS inventory NH3 emissions used in the inversions and significantly higher (more than by a factor for two) when compared to two other global bottom-up inventories, CAMS and CAMEO. The regional NH3 emissions estimates derived from our global inversion are also assessed through comparisons with other inventories and recent top-down estimates based on the satellites NH3 observations. Our estimates of the NH3 emissions at both the global and regional scales are mostly consistent with other top-down inversion estimates. 

How to cite: Kumar, P., Ciais, P., Hauglustaine, D., Broquet, G., Clarisse, L., Van Damme, M., and Coheur, P.: Inversion of the global NH3 emissions (2019-2022) based on IASI NH3 observations and the LMDZ-INCA chemistry-transport model , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18036,, 2024.

On-site presentation
Adrian Jost, Steffen Beirle, Christian Borger, Nicolas Theys, Steffen Ziegler, and Thomas Wagner

We provide a global database of SO2 emissions from point sources generated from TROPOMI observations of SO2 (COBRA product) for the time range from May 2018 to July 2022. Our algorithm derives the advection of SO2 by combining TROPOMI SO2 column densities and ERA5 wind fields, i.e., taking the product of the vertical column density gradient and the horizontally projected wind speed. In addition, several corrections, e.g., for satellite sensitivity and topography, are applied. For each point source, error estimates are given, considering the uncertainties of the various retrieval steps.

A fully automated iterative detection algorithm of point sources from around the world forms the basis of our catalog. The catalog includes a list of 130 locations identified as substantial anthropogenic SO2 point sources. Most of these locations are close to power plants included in the Global Power Plant Database (GPPD) or match entries in previously compiled SO2 inventories.

The emissions in our catalog are in good agreement (Pearson correlation coefficient (r) of 0.82) with those recorded in existing SO2 datasets (Fioletov et al., 2023) but are higher by about 36%.

By comparing our SO2 catalog with matches in the global NOx catalog compiled by Beirle et al. (2023), information on the used fuel and applied filtering measures is provided. We observe an SO2 to NOx mass ratio ranging from 0.8 to 141.5 with a mean of about 10 for the selected point sources.

The SO2 catalog was created as part of the World Emission (2022) project, funded by ESA, which focuses on quantifying emissions of different species that can be detected by satellite instruments. The complete SO2 catalog will be made publicly available through the World Emission Portal at

How to cite: Jost, A., Beirle, S., Borger, C., Theys, N., Ziegler, S., and Wagner, T.: Improving global SO2 emission inventories using Sentinel-5P TROPOMI satellite data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18365,, 2024.

On-site presentation
Nalini Krishnankutty, Rona L. Thompson, Ignacio Pisso, Philipp Schneider, Kerstin Stebel, Motoki Sasakawa, and Stephen M. Platt

We present a novel and efficient method for atmospheric inversions of satellite observations using a Lagrangian Particle Dispersion Model (LPDM) and demonstrate its use for a case study in Siberia. LPDMs have several advantages over Eulerian models. First, they can more precisely represent an observation since calculations are independent of a computational grid and second, LPDMs can be run in a backwards in time mode, which allows the computation of the sensitivity of an observation to fluxes and in this way are sometimes said to be “self adjoint”. The LPDM used in our study is FLEXPART.

In our method, FLEXPART is run in a backwards-in-time mode to determine total column source-receptor relationships (SRRs), which describe the relationship between a total column observation (such as from a satellite) and fluxes. The SRRs are used in the Bayesian inversion framework, FLEXINVERT, to optimize fluxes over a nested domain. Background mixing ratios for the total column observations are determined by coupling FLEXPART backward trajectories with the outputs of an optimized global Eulerian model (TM5).

We demonstrate the method in a case study, determining CH4 emissions over Siberia using observations from the TROPOspheric Monitoring Instrument (TROPOMI) onboard Sentinel 5P. Siberia was chosen as it is a region with important emissions from oil/gas facilities and coal mining, as well as abundant natural sources from wetlands. The posterior fluxes obtained using TROPOMI XCH4 are evaluated by comparing to inversions using observations from the ground-based network, JR-STATION.

How to cite: Krishnankutty, N., Thompson, R. L., Pisso, I., Schneider, P., Stebel, K., Sasakawa, M., and Platt, S. M.: An efficient use of a Lagrangian transport model for atmospheric inversions using satellite observations: case study using TROPOMI to estimate CH4 emissions over Siberia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3175,, 2024.

On-site presentation
Zhao-Cheng Zeng, Bruno Franco, Lieven Clarisse, Lu Lee, Chengli Qi, and Feng Lu

Formic acid (HCOOH) is one of the most abundant volatile organic compounds (VOCs) in Earth’s atmosphere and an important source of atmospheric acidity. Satellite observations play an indispensable role in improving our understanding of global HCOOH sources and sinks. However, existing polar-orbiting satellites that are sensitive to tropospheric HCOOH provide only two daily overpasses over the same location, one during the day and the other at night. The diurnal changes of tropospheric HCOOH are therefore under-constrained, limiting our ability to monitor its evolution and transport throughout the troposphere. The Geostationary Interferometric Infrared Sounder (GIIRS) onboard China’s FengYun-4 satellite series is the world’s first geostationary hyperspectral infrared sounder. Here, we present the first retrieval of HCOOH from GIIRS onboard FengYun-4B. Results from July 2022 to June 2023 highlight the seasonal variation of the HCOOH distribution in Asia driven by biomass burning emissions and biogenic sources. Sensitivity to HCOOH peaks during daytime and decreases at night, following diurnal changes of thermal contrast between the surface and the atmosphere. FY-4B/GIIRS in the geostationary orbit will offer important information with its high temporal resolution to improve our understanding of the production, evolution, and loss processes of HCOOH in the atmosphere. Furthermore, cross-validation with IASI HCOOH data shows good agreement, indicating that observations from FY-4B/GIIRS have comparable sensitivity to IASI.

How to cite: Zeng, Z.-C., Franco, B., Clarisse, L., Lee, L., Qi, C., and Lu, F.: Observing a Volatile Organic Compound from a Geostationary Infrared Sounder: HCOOH from FengYun-4B/GIIRS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4816,, 2024.

On-site presentation
Rimal Abeed, Audrey Fortems-Cheiney, Grégoire Broquet, Robin Plauchu, Isabelle Pison, Antoine Berchet, Elise Potier, Gaëlle Dufour, Adriana Coman, Dilek Savas, Guillaume Siour, Henk Eskes, and philippe ciais

In 2020, China’s response to the COVID-19 breakdown included strict regulations on mobility in several provinces. Multiple studies showed that these measures caused a decrease in the emissions of nitrogen oxides NOx (= NO + NO2). In this study, we exploit the high spatial resolution and coverage of the TROPOMI nitrogen dioxide (NO2) observations, over Eastern China, in order to provide an estimate of this decrease down to the level of provinces. We assimilate these observations in NOx atmospheric inversions for the years 2019 through 2021, based on the variational inversion drivers of the Community Inversion Framework (CIF), coupled to a 0.5° resolution  configuration  of the CHIMERE regional chemistry transport model for the North Chinese Plain region, and of  its adjoint (both including the MELCHIOR-2 chemistry scheme). This framework allows to control the emissions at 0.5° resolution, and then to target emissions at province scale, but also to account for a full chemistry scheme in the atmospheric process. The prior estimate of the anthropogenic emissions for this Bayesian inversion framework is based on a combination of the Carbon-Monitor and CEDS inventories, accounting for the day-to-day variations of these emissions. The corrections of the prior anthropogenic and natural emissions allows to decrease the misfits to the TROPOMI NO2 observation by up to 50%, so that the inverted emissions are highly consistent with these satellite data. Furthermore, the satellite coverage of the domain is good, with more than 60% of the model domain observed 95% of the days. Our results show a decrease in NOx emissions observed in most of Eastern China, during January, February, and March 2020, reaching -40% in February 2020 as compared to 2019. In some Chinese provinces, such as Shanghai, Qinghai, Jiangsu, Hubei and Henan, the reduction in NOx emissions accounted for -38%, -29%, -31%, -36%, and -24% respectively. In North Eastern China, however, our results show an increase in the NOx emissions in three major provinces: Jilin (+11.35% in January 2020), and Liaoning (+16.33% in March 2020). The yearly total emissions of NOx in Eastern China were slightly lower in 2020 than those in 2019, with emissions of 15.58 and 15.76 TgNO2/year, respectively. While in 2021, the total emissions of NOx accounted to16.42 TgNO2/year. We compared the emissions in 2021 to those in 2019, and we found that the levels are higher in most of China, especially in February reaching +45% in the North East, for instance. We show that our results are consistent with other studies that focused on the change in NOx emissions in China, during the COVID-19 lockdown period.

How to cite: Abeed, R., Fortems-Cheiney, A., Broquet, G., Plauchu, R., Pison, I., Berchet, A., Potier, E., Dufour, G., Coman, A., Savas, D., Siour, G., Eskes, H., and ciais, P.: The impact of the lockdown during the COVID-19 pandemic outbreak on NOx pollution in China, as derived from TROPOMI and variational atmospheric inverse modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20582,, 2024.

On-site presentation
Jianan Chen

Ammonia (NH3) plays a crucial role in the formation of PM2.5 as a primary alkaline gas in the atmosphere. An NH3 emission inventory is an essential component of numerical chemical transport models for scenario simulations and developing mitigation strategies. The significantly NH3 hotspots located in China can be seen both in compiled inventories and in satellite observations. However, almost all emission inventories report that NH3 emissions from China have a large uncertainty. In our research, we conducted a top-down optimization of monthly NH3 emission over China using IASI-derived surface NH3 concentration and the CAMx model. First, IASI-derived surface NH3 concentrations are assessed by comparing against a surface monitoring network (NNDMN) in China during 2020. Second, an optimal estimation method is used to assimilate observations to optimize the NH3 priori emissions. The posteriori NH3 emissions are approximately double the priori estimates from the prior MEIC inventory and indicate potential underestimation over hotspot areas, especially during the warm months. Monthly variations in posteriori emissions exhibited significant differences across 6 regions of China, with peak emissions occurring in May and July, and relatively stable levels observed in the southern regions of China. In conclusion, this analysis enhanced the understanding of the spatial-temporal patterns of regional NH3 emissions in China, which is important for the development of mitigation strategies to address consistently high NH3 emissions in China.

How to cite: Chen, J.: Inversion of monthly ammonia emissions in China by assimilating satellite surface observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6173,, 2024.

Virtual presentation
Frank Werner, Kevin W. Bowman, Vivienne Helen Payne, James Lester McDuffie, and Valentin Kantchev

Advances in sensor technology have led to a substantial increase in the data output from satellite-borne remote sensing instrumentation. For example, NASA’s Cross-track Infrared Sounder (CrIS) and Atmospheric Infrared Sounder (AIRS) provide millions of global, spectrally-resolved radiance observations every day. It is becoming increasingly challenging to process these large data sets and perform the subsequent composition profile retrievals for all observations. Indeed, NASA’s TRopospheric Ozone and its Precursors from Earth System Sounding (TROPESS) project, which produces records of atmospheric constituents from multiple satellite and ground data through a common retrieval algorithm, can only process about 1% of the sampled CrIS observations.

This talk presents efforts to process all the observed CrIS and AIRS data by applying machine learning techniques. In particular, we present staggered artificial neural networks (ANNs) that can reliably replicate the retrieved CrIS carbon monoxide and ammonia profiles, as well as important retrieval diagnostics such as the retrieval error and averaging kernels. Once trained, these ANNs can perform predictions for millions of CrIS radiance observations in minutes. This new data set not only covers the gaps in the global retrievals of composition fields, but also provide uncertainty and variability information on very small scales.

How to cite: Werner, F., Bowman, K. W., Payne, V. H., McDuffie, J. L., and Kantchev, V.: Using Machine Learning to Predict Column Concentrations and Retrieval Diagnostics of the TROPESS Atmospheric Composition Profiles, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21179,, 2024.

Posters on site: Thu, 18 Apr, 10:45–12:30 | Hall X5

Display time: Thu, 18 Apr 08:30–Thu, 18 Apr 12:30
Chairpersons: Camille Viatte, Andreas Richter, Pieternel Levelt
Steffen Beirle and Thomas Wagner

The divergence, i.e. the spatial derivative of the horizontal flux, yields the local balance of sources of sinks. Strong positive divergence is observed for (and allows to quantify) NOx emissions from point sources like power plants. Within the downwind plume, NO2 changes due to (a) further NO to NO2 conversion (NO2 source, positive divergence) and (b) NO2 reaction with OH (NO2 sink, negative divergence).

In this study we aim to disentangle and quantify these competing effects based on the divergence of the observed NO2 flux. We focus on large and isolated power plants where additional sources are negligible. Goal is to determine the time scales for the NO to NO2 conversion and the NO2 lifetime for power plant plumes.

How to cite: Beirle, S. and Wagner, T.: Investigating NO2 processing in power plant plumes from TROPOMI, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2121,, 2024.

Hao Kong, Jintai Lin, Yuhang Zhang, Sijie Wang, and Chenghao Xu

High-resolution spaceborne emission inversions play a crucial role in independent emission monitoring, small-scale pollution modelling, and exposure estimation. However, spaceborne emission inversion at 1-km resolution is still a challenge due to the insufficiency of satellite observations, along with limitations such as computational costs and meteorological data. The spatial resolutions of existing satellite-based NO2 observations (e.g. TROPOMI: nadir pixel of ~3.5×5.5 km2) fall short in capturing spatial features at 1-km resolution. Here we develop an innovative technique to integrate high-resolution geodata in emission inversions. This technique introduces constraints based on geodata associated with emissions to inversions independent of predefined downscaling schemes. Our inversions show advanced results of NOx emissions with detailed spatial patterns at small scale, especially for sources relevant to traffic and marine shipping which are of large uncertainties in current inventories.

How to cite: Kong, H., Lin, J., Zhang, Y., Wang, S., and Xu, C.: 1-km resolution inversion of NOx emissions based on satellite constrained by geodata, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2865,, 2024.

Amir Souri, Gonzalo González Abad, Glenn Wolfe, Matthew Johnson, Bryan Duncan, and Tijl Verhoelst

Questions about how regulations have shaped ozone pollution regionally cannot be answered by studying observed surface ozone concentrations alone, as we must precisely determine ozone production rates, which refer to the amount of ozone molecules photochemically produced in the atmosphere. Through an extensive suite of NASA's airborne campaigns such as DISCOVER-AQs, KORUS-AQ, INTEX-B, SENEX, and ATOMs, constraining a well-characterized chemical box model, we establish a simple but robust relationship between ozone production rates and various observable parameters; some of these factors, fortunately, are being measured or constrained by satellite observations, which has allowed us to create the first-ever maps of ozone production rates across the globe. We quantitatively and qualitatively assess this product's efficacy through independent airborne campaigns and by contrasting extreme events to a norm. We have a clear path forward to enhance this innovative product using agile machine learning algorithms for the years from 2005 to 2024, along with its well-characterized error budget.

How to cite: Souri, A., González Abad, G., Wolfe, G., Johnson, M., Duncan, B., and Verhoelst, T.: Early Results of Ozone Production Rate Estimates Using Satellite Observations: Insights From Numerous NASA Atmospheric Composition Campaigns, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3562,, 2024.

Xiaohan Wang, Chengxin Zhang, and Cheng Liu

Nitrogen dioxide (NO2) in the lower marine atmosphere, mainly emitted by maritime shipping, plays a crucial role in air pollution formation and global human health. However, few measurements of marine atmospheric NO2 hinder knowledge of trace gas trends and atmospheric chemistry evolution due to shipping emissions. In this study, we use long-term satellite observations of tropospheric NO2 column from the European TROPOspheric Monitoring Instrument (TROPOMI) and the Chinese Environmental trace gases Monitoring Instrument (EMI) to analyze marine atmospheric NO2 variations, especially during the global COVID-19 pandemic and escalating geopolitical crises. First, we demonstrate the detection of NO2 enhancements along shipping routes, including the North Atlantic route, the North Pacific route, and the Cape route, indicating significant emissions of atmospheric NO2 from on-ocean shipping. Second, we observe and quantify the response of marine atmospheric NO2 concentrations to major shipping events, such as the Suez Canal blockage, the Los Angeles-Long Beach port congestion, and the Russia-Ukraine war, resulting in local NO2 concentration variations of approximately 40% decrease to 70% increase. Long-term analysis reveals reduced NO2 concentrations in most coastal ports and maritime shipping routes during the COVID-19 lockdown, with reductions exceeding 50% or durations lasting up to 200 days. However, some rapidly developing ports, such as Beibu Gulf (China) and Dakar (Senegal), did not experience a decrease in NO2 concentrations, suggesting that local authorities need to pay more attention to these fast-growing yet underestimated emission sources. In addition, by excluding the impact of meteorology using statistical models, we find that the current Emission Control Area (ECA) policies have effectively reduced NO2 concentrations in Chinese coastal ports. These results contribute to understanding spatiotemporal characteristics of marine atmospheric NO2, including ports and open-sea shipping routes, and guide further ECA policies to control marine NO2 pollution.

How to cite: Wang, X., Zhang, C., and Liu, C.: Satellite unravels recent changes in atmospheric nitrogen oxides emissions from global ocean shipping, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4517,, 2024.

YiZhou Xu, WenJing Su, and Cheng Liu

Formaldehyde (HCHO) is a toxic and harmful air pollutant to humans, animals, and plants and is an essential precursor of PM2.5 and ozone compound pollution. Few studies have focused on HCHO in Tibet, the third pole with a unique ecosystem that requires protection. Here, we investigate the spatial-temporal distribution of HCHO from 2013 to 2021 and its influencing factors from satellite observations in Tibet. We found that the average HCHO VCD in Tibet presents a significant annual growth rate of 2.25%/yr, which is similar to that in India and even higher than that in most of the world, including eastern China. Moreover, HCHO VCD in the eastern region of Tibet shows no seasonal pattern, unlike other areas. The anomalous variation in HCHO concentrations in Tibet is primarily attributed to long-distance transnational transport from incomplete combustion in India Assam. Our results help strengthen concerns about atmospheric environmental management in Tibet.

How to cite: Xu, Y., Su, W., and Liu, C.: Unexpected HCHO transnational transport: Influence on the temporal and spatial distribution of HCHO in Tibet from 2013 to 2021 based on satellite, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4826,, 2024.

Ruibin Xue, Shanshan Wang, and Bin Zhou

In this study, TROPOspheric Monitoring Instrument (TROPOMI) observations were resampled to obtain 0.01° × 0.01° NO2 VCD (vertical column density) of Yangtze River Delta (YRD), China. The adjusted Exponentially-Modified Gaussian (EMG) model was improved to estimate the quantified nitrogen oxides (NOX) emission. The estimation in typical cities under regionally polluted YRD area has a good correlation with Multi-resolution Emission Inventory for China (MEIC) emission with R more than 0.9 but lower results mainly due to the underestimation of NO2 VCD by TROPOMI in polluted areas. On this basis, using the adjusted EMG method, this study quantified NOX emission in Shanghai during 2022 lockdown period as 32.60 mol/s with a decrease of 50–80%, which was mainly contributed by the transportation and industrial sectors. The significant reduction of NOX emission in Shanghai is much higher than that of volatile organic compounds (VOCs), which led to dramatic changes in formaldehyde-to-nitrogen dioxide ratio (HCHO/NO2, FNR). Thus, when enforcing regulation on NOX emission control in the future, coordinately reducing VOCs emission should be implemented to mitigate urban O3 pollution.

This work was supported by Sino-German Mobility Program (M-0509) and National Natural Science Foundation of China (grant number 42075097, 22176037, 42375089, 22376030).

How to cite: Xue, R., Wang, S., and Zhou, B.: Assessing NOX emission reduction of Shanghai during city-wide lockdown from TROPOMI high spatial resolution observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5854,, 2024.

Liudmyla Malytska, Evgenia Galytska, Annette Ladstätter-Weißenmayer, John P. Burrows, and Stanislav Moskalenko

Apart from the loss of life and property, the hostilities, which started on February 24, 2022, with the invasion by Russian armed forces into Ukraine, are altering Ukraine’s environment. In this study, we will present the major findings of Malytska et al., 2024, discussing the changes in tropospheric pollution, specifically nitrogen dioxide (NO2), as a consequence of military activities. This study uses the TROPOspheric Monitoring Instrument (TROPOMI) and Visible Infrared Imaging Radiometer Suite (VIIRS) satellite observations, Global Fire Assimilation System (GFAS) wildfire emission inventory, European Centre for Medium-Range Weather Forecasts (ECMWF) daily ERA5 reanalysis data, and the Hybrid Single-Particle Lagrangeian Integrated Trajectory analysis model (HYSPLIT) 5.2 to quantify the spatiotemporal distribution of tropospheric NO2, its changes and transport during the first three months of the armed conflict in Ukraine. This provides insights into the impact of hostilities on local air quality, as well as regional and transborder pollution.

We discuss NO2 variability with a particular emphasis on comparing periods before and during hostilities to differentiate the effects of COVID-19 restrictions and the hostilities on NO2 emissions over Ukraine. The retrieved emissions show a temporal reduction in NO2 emission in industrial areas, comparable to the COVID-19 pandemic lockdown, whereas the NO2 tropospheric vertical column locally increased in the areas of conflict. Based on the TROPOMI and VIIRS data, we linked the major fires caused by the conflict to air pollution and found that hostilities led to more frequent and intense fires in conflict zones deteriorating air quality in the region. To investigate the impact of the hostilities on atmospheric pollution, we analysed nitrogen oxide (NOx) emission and injection altitude of fire, using the GFAS data. It was found that fires in conflict-affected areas exhibit greater intensity, characterized by larger plume top heights and higher rates of emission, in comparison to fires located far from the front line or resulting from isolated strikes. To demonstrate that increased fire activities contribute to pollution at both local and regional levels, we provide a case study of the fire episode of March 19-23, 2022, in the Kyiv region, coinciding with the active stage of the conflict and the defense of the capital, Kyiv. The simulations of HYSPLIT version 5.2 forward trajectories model showed that a smoke-particle-included air mass, related to the fires in the Chornobyl Exclusion Zone, was transported to Poland and countries of the Baltic region at the height of 1.5-3 km within 72 hours. A plume of NO2, which originated from fires in the Chornobyl Exclusion Zone on March 20, 2022, was observed in Poland the following day.


Malytska L., Ladstätter-Weißenmayer A., Galytska E, and. Burrows J.P. Assessment of environmental consequences of hostilities: Tropospheric NO2 vertical column amounts in the atmosphere over Ukraine in 2019–2022. Atmospheric Environment 318 (2024) 120281, DOI:

How to cite: Malytska, L., Galytska, E., Ladstätter-Weißenmayer, A., Burrows, J. P., and Moskalenko, S.: Tropospheric NO2 changes in Ukraine (2019–2022) amidst the Russian-Ukrainian conflict and consequent transboundary effects, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7964,, 2024.

Camille Viatte, Nadir Guendouz, Clarisse Dufaux, Arjan Hensen, Daan Swart, Martin Van Damme, Lieven Clarisse, Pierre Coheur, and Cathy Clerbaux

Ammonia (NH3) is an important air pollutant which, as precursor of fine particulate matter, raises public health issues. This study analyzes 2.5-years of NH3 observations derived from ground-based (miniDOAS) and satellite (IASI) remote sensing instruments to quantify, for the first time, temporal variabilities (from interannual to diurnal) of NH3 concentrations in Paris.

The IASI and miniDOAS datasets are found to be in relatively good agreement (R>0.70) when atmospheric NH3 concentrations are high and driven by regional agricultural activities. Over the investigated period (January 2020 – June 2022), NH3 average concentrations in Paris measured by the miniDOAS and IASI are 2.23 μg.m-3 and 7.10x1015, respectively, which are lower or equivalent to those documented in other urban areas. The seasonal and monthly variabilities of NH3 concentrations in Paris are driven by sporadic agricultural emissions influenced by meteorological conditions, with NH3 concentrations in spring up to 2 times higher than in other seasons.

The potential source contribution function (PSCF) reveals that the close (100-200km) east and northeast regions of Paris constitute the most important potential emission source areas of NH3 in the megacity.

Weekly cycles of NH3 derived from satellite and ground-based observations show different ammonia sources in Paris. In spring, agriculture has a major influence on ammonia concentrations and, in the other seasons, multi-platform observations suggest that ammonia is also controlled by traffic-related emissions.

In Paris, the diurnal cycle of NH3 concentrations is very similar to the one of NO2, with morning enhancements coincident with intensified road traffic. NH3 evening enhancements synchronous with rush hours are also monitored in winter and fall. NH3 concentrations measured during the weekends are consistently lower than NH3 concentrations measured during weekdays in summer and fall. This is a further evidence of a significant traffic source of NH3 in Paris.

How to cite: Viatte, C., Guendouz, N., Dufaux, C., Hensen, A., Swart, D., Van Damme, M., Clarisse, L., Coheur, P., and Clerbaux, C.: Ammonia in Paris derived from ground-based open-path and satellite observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8072,, 2024.

Lorenzo Fabris, Nicolas Theys, Lieven Clarisse, Hugues Brenot, Huan Yu, Jeroen van Gent, Jonas Vlietinck, and Michel Van Roozendael

Sulfur dioxide (SO2), emitted from volcanic eruptions, can have a major impact on the environment and society. While nadir-viewing satellites have been providing precise information on its Vertical Column Density (VCD) for several decades, the retrieval of its Layer Height (LH) is a more recent development, although it is important for the aviation safety, estimation of SO2 emissions, understanding of volcanic processes and climate research. In the Ultraviolet (UV), the current algorithms are often time-consuming and still lack sensitivity, especially in the presence of aerosols. 

Our research aims at developing an improved SO2 LH (and VCD) retrieval algorithm for the TROPOspheric Monitoring Instrument (TROPOMI). While the third spectral band of TROPOMI is traditionally used for sulfur dioxide, a shorter UV region has been exploited here to take advantage of the strong absorption of SO2 in the second band. As a demonstration case, Slant Column Density (SCD) retrievals in band 2 were carried out using the Covariance-Based Retrieval Algorithm (COBRA) [1]. We show that SO2 SCDs from both spectral bands are generally in excellent agreement. However, the results in band 2 reveal a greater sensitivity to SO2 than in band 3.

Motivated by this result, we performed SO2 plume height retrievals on an extensive set of synthetic spectra representative of TROPOMI observation conditions, using the Look-Up Tables Covariance-Based Retrieval Algorithm (LUT-COBRA) [2]. The SO2 LHs and VCDs we find from the second band are more accurate, and the associated retrieval errors appear to be considerably reduced in comparison to those of the band 3.

In addition, sensitivity analyses were conducted to further characterise the wavelength dependence and effect of some observation conditions on the quality of these retrievals. More specifically, we assess the impact of the temperature, air density, ozone profile and VCD, SO2 absorption cross sections, surface albedo and height as well as the SO2 profile shape. 

Finally, we present the next steps to further develop the LUT-COBRA approach and application to TROPOMI band 2 measurements. 


[1] N. Theys et al. Atmospheric Chemistry and Physics, 21(22):16727–16744, 2021.
[2] N. Theys et al. Atmospheric Measurement Techniques, 15(16):4801–4817, 2022.

How to cite: Fabris, L., Theys, N., Clarisse, L., Brenot, H., Yu, H., van Gent, J., Vlietinck, J., and Van Roozendael, M.: Sensitivity tests for improved retrievals of SO2 plume height from TROPOMI observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8314,, 2024.

Yutao Chen, Ronald van der A, Jieying Ding, Henk Eskes, Jason Williams, Thanos Tsikerdekis, and Pieternel Levelt

This study aims to constrain SO2 emissions during 2018-2023 from satellite measurements by utilizing an improved flux-divergence method and estimated local monthly averaged SO2 lifetimes. The local SO2 lifetime incorporating SO2 chemical loss and dry deposition is calculated to derive the sink term of SO2. The derived SO2 lifetime in India shows seasonality, with longer lifetime (19 hours on average) in winter and shorter lifetime (12 hours on average) in summer. The inclusion of this non-constant lifetime improves the precision of estimating Indian SO2 emissions when compared to calculations using a constant SO2 lifetime. Our implementation of the divergence method improves its spatial resolution. With this improvement on the resolution, the smoothing of the source locations is mitigated.  Finally, the annual total SO2 emissions of India is estimated to be 6.5 Tg year-1, which is in the middle of the range of emissions of previous inventories.  Opposite to the continue increasing trend anticipated in previous studies, the SO2 emissions first decreased in 2020, while increasing in 2021 to 2023. The lower emissions in 2020 might be a result of the COVID-19 quarantine measures.

How to cite: Chen, Y., van der A, R., Ding, J., Eskes, H., Williams, J., Tsikerdekis, T., and Levelt, P.: SO2 emissions in India derived from TROPOMI observations using the flux-divergence method and local SO2 lifetimes., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8487,, 2024.

Nga Ying Lo, Matthias Schneider, Kanwal Shahzadi, Frank Hase, Peter Braesicke, René Caspart, and Achim Streit

The development of MUSICA IASI processing was initiated as part of the MUSICA (Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) project funded by the European Research Council. This processor works with IASI (Infrared Atmospheric Sounding Interferometer) radiances measured under cloud-free conditions, and, using optimal estimation, derives vertical distributions of water vapor, ratios between water vapor isotopologues, and several trace gases including greenhouse gases, methane and nitrous oxide. In accordance with the FAIR (findable, accessible, interoperable, reusable) principles, all MUSICA IASI products are freely available together with their observation specific averaging kernels and uncertainty covariances. Recently, retrievals of sulfur dioxide (SO2), peroxyacetyl nitrate (PAN), acetic acid and acetone have been included, in order to account for their important spectroscopic signals in case of volcanic eruptions and biomass burning events, respectively. 


Here, we present the MUSICA IASI SO2 retrieval setup. A particularity is the use of a logarithmic SO2 concentration scale, which facilitates a reliable detection of the altitude where the SO2 plume is situated (retrieved from the spectral signal, no a priori assumptions of an SO2 plume height required). We document the superiority of this retrieval setup compared to a retrieval on a linear SO2 concentration scale. In addition, we empirically demonstrate the quality of the SO2 profile data in the preliminary results of three different volcano eruption events at three different latitude regions: 2019 Raikoke (48°N), 2021 La Palma (Cumbre Vieja, 29°N), and 2022 Hunga Tonga-Hunga Ha’apai (20°S). The amount of SO2 and the SO2 plume height are different for the three events. We show that the MUSICA IASI product is able to correctly capture these differences.


The availability of individual averaging kernels allows a quantitative inter-comparison to other SO2 data products. For SO2 plumes in the low and middle troposphere, we will explore respective comparison possibilities to data obtained from Ticosonde in-situ measurements. For SO2 plumes in the upper troposphere or stratosphere, we plan to use data provided by MLS (Microwave Limb Sounder instrument aboard the NASA/Aura satellite). IASI SO2 products generated by other processors and TROPOMI/S5P SO2 products will also be potential candidates for inter-comparison studies.

How to cite: Lo, N. Y., Schneider, M., Shahzadi, K., Hase, F., Braesicke, P., Caspart, R., and Streit, A.: Retrieval of vertical concentration profiles of SO2 using the IASI satellite instrument, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9075,, 2024.

Nejla Eco, Sébastien Payan, and Laurence Croizé

On board of MetOp satellite series is Infrared Atmospheric Sounding Interferometer (IASI), a Fourier Transform, Michelson-based spectrometer which aims to provide a high-resolution atmospheric emission spectrum to derive temperature and humidity profiles with high spectral resolution. Having been operational since 2006, this spectrometer has been exploited for numerous research articles and can serve as a reliable reference instrument. We will use IASI archive to test the retrieval approach in the Fourier space which we believe is well suited for analysis of a large set of spectra to be recorded by next generation spatial tropospheric sounder as MTG-IRS.   

The technique of partially scanned interferograms applied to the retrieval of trace gases from the IASI was rarely used. However, there exist works that indicate the potential of this methodology for the specific cases of CO, CO2, CH4 and N2O that should allow us to retrieve trace gases column abundances at an unprecedented accuracy and at the level of the single IASI footprint. As IASI interferograms are not available, we must transform the IASI spectra back to the interferogram domain and identify regions sensitive to the single gas species. The retrieval is then performed using Least Squares estimation to these small segments of interferometric radiances. The expected advantage to the usual methods (retrieval in the spectral domain) is an efficient use of the information contained in all the IASI channels that are available in the absorption bands of a specific gas species. We will present the first step of our study on the retrieval of CO from partial interferogram of IASI observations. More specifically, the set of simulations of IASI interferograms that will be noised and then used for CO retrievals.

The simulation of IASI spectra, was performed using LATMOS Atmospheric Retrieval Algorithm (LARA), a robust and affirmed radiative transfer model. [Segonne at al., 2021] LARA was conjoined with the TIGR, a climatological library of atmospheric situations representing the Earth’s atmosphere called the Thermodynamic Initial Guess Retrieval (TIGR). [Chédin et al., 1985]. Each atmospheric situation is described by values of temperature, water vapor and ozone concentrations for a given pressure grid, from the ground surface to the TOA (top of the atmosphere). This case study includes all of the 2311 TIGR profiles available. Furthermore, the study considers carbon monoxide, a trace gas crucial for understanding both the air quality and climate forcing. Carbon monoxide typically appears in the range of 2050 to 2350 cm-1 wavenumber, with its characteristic “comb” shaped absorption signature. [Serio et al.,2012]The simulations are performed for surface temperatures ranging from -15 to 15 K in steps of 5 K from the base surface temperature, to explore the impact of thermal contrast. [Baudin et al., 2016]. Expected are number of radiance simulations in the CO-corresponding wavelength range, obtained by using LARA. Finally, FFT (Fast Fourier Transform) of simulated radiances are generated, leading to a 130 000 spectra interferogram dataset on which statistical analysis of CO signatures will be presented. If applicable, first full CO retrieval from the dataset should be presented.

How to cite: Eco, N., Payan, S., and Croizé, L.: Towards retrieval of CO from MTG-IRS in the Fourier space with IASI as a demonstrator   , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9814,, 2024.

Nadir Guendouz, Camille Viatte, Anne Boynard, Sarah Safieddine, Carsten Standfuss, Solène Turquety, Martin Van Damme, Lieven Clarisse, Pierre Coheur, Raymond Armante, Pascal Prunet, and Cathy Clerbaux

Ammonia (NH3) is an atmospheric pollutant mainly emitted by the agricultural sector, which has an effect on public health since it is a precursor of fine particles (PM2.5). The diurnal variability of NH3 in the atmosphere and its transformation into particles are poorly constrained and strongly depend on meteorological parameters, in particular temperature. This strongly influences our ability to correctly simulate NH3 emissions and associated particulate pollution events in atmospheric models

The IRS (InfraRed Sounder) instrument which will be launched on the MTG (Meteosat Third Generation) satellite into geostationary orbit in late 2024, will offer the ability to evaluate NH3 diurnal variabilities and its dependence on atmospheric temperature with frequent measurements (every 30-45 minutes over Europe and Africa) and fine spatial resolution (4 km x 4 km at the Equator and Greenwich meridian).

This work shows the potential of the European geostationary IRS-MTG mission to capture the spatio-temporal variability of ammonia and temperature focusing on a case study over the Brittany region in France. Synthetic spectra are simulated from the 4A/OP radiative transfer model using atmospheric states derived from the CHIMERE chemistry-transport model. The IRS NH3 observations are compared to the current IASI observations in terms of vertical sensitivity and error budget. The uncertainty analysis over the Brittany region is calculated using NH3 Jacobians computed from the 4A/OP radiative code and the noise covariance matrix provided by each satellite.

How to cite: Guendouz, N., Viatte, C., Boynard, A., Safieddine, S., Standfuss, C., Turquety, S., Van Damme, M., Clarisse, L., Coheur, P., Armante, R., Prunet, P., and Clerbaux, C.: Assessing the future IRS-MTG NH3 and temperature observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10410,, 2024.

Santiago Parraguez Cerda, Johann Rasmus Nüß, Nikos Daskalakis, Oliver Schneising, Michael Buchwitz, Mihalis Vrekoussis, and Maria Kanakidou

Methane (CH4) is an important greenhouse gas (GHG), contributing about ~23% (0.62 W m-2) of the additional radiative forcing on the troposphere due to its increased concentrations compared to pre-industrial levels. Mainly, anthropogenic sources of CH4 are agriculture, livestock farming, fossil fuels and biomass burning. Further, natural sources are primarily wetlands, while minor ones are oceans, termites, wild animals and permafrost. There are persistent uncertainties regarding the sources of CH4 due to limited knowledge of the processes underlying them, leading to inconsistencies between top-down and bottom-up estimates. It is relevant to reduce these uncertainties and accurately assess CH4 emissions as it is meaningful for atmospheric modelling, climate change estimations, and policy making. Higher resolution and lower uncertainty data can benefit assimilation systems, thus increasing confidence in estimates of emission sources.

This work aims to assimilate high-resolution data from satellite observations and measurements obtained from surface stations to optimize global methane emission fields. We evaluate differences resulting from the assimilation of satellite observations at varying resolutions. Additionally, we compare different setups of the assimilation framework, using varied combinations of satellite and surface measurements, to assess potential discrepancies in the resulting emissions. The modelling framework is based on the TM5-MP (massive parallel) atmospheric chemistry-transport model, utilizing its adjoint in a four-dimensional (4DVAR) data assimilation system. Our study aims to constrain global CH4 emissions first at a spatial resolution of 3° × 2° (longitude × latitude) for 2018 and then increase the resolution to 1° × 1°. The tropospheric CH4 mixing ratio product slated for assimilation is acquired by the TROPOMI instrument onboard the satellite Sentinel 5-P, and retrieved using the weighting function modified differential optical absorption spectroscopy (WFMD-IUP) algorithm. This product offers enhanced coverage, especially over higher latitudes, and reduced uncertainty compared to the operational product. Conversely, near-surface CH4 measurements are obtained from stations within the global NOAA network. Preliminary results suggest a relevant role of both the resolution of the satellite instrument and the type of data assimilated regarding convergence and final results.

How to cite: Parraguez Cerda, S., Nüß, J. R., Daskalakis, N., Schneising, O., Buchwitz, M., Vrekoussis, M., and Kanakidou, M.: Comparison of inversions of global methane emissions using TM5-MP/4DVAR with TROPOMI measurements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10777,, 2024.

Deborah Claire Stein Zweers, Maarten Sneep, and Martin de Graaf

With more than 5 years of operational aerosol index data from the TROPOMI instrument onboard the Sentinel 5-precursor (S5P), the seasonal cycle can be characterized and trends in global aerosol index can be investigated in more depth. Positive values of the aerosol index are driven by strong emission and transport events of ultraviolet (UV) absobring aerosols including desert dust outbreaks, biomass burning smoke, and volcanic ash eruptions. Near-zero values of the aerosol index however can also be useful to understand the dependency and sensitivity of calculated reflectances on precision and nature of the calibration of the instrument. Since the reprocessing of the dataset carried out in 2023, the largest effects of observed degradation in radiance and irradiance have been well characterized and are removed. A discussion will be presented addressing the delineation of variability due to changes in the global emission of absorbing aerosols as well as observed and characterized changes in insturment sensitivity and calibration.  As a comparison the soon-to-be released OMI aerosol index data (Collection 4) extending back to 2004 will be appended to lend additional insights about long-term variability seasonal variability of UV-absorbing aerosol presence. 

How to cite: Stein Zweers, D. C., Sneep, M., and de Graaf, M.: Evaluating trends using TROPOMI and OMI aerosol index, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10888,, 2024.

Swathi Maratt Satheesan, Kai-Uwe Eichmann, and Mark Weber

Tropospheric ozone, a critical pollutant and greenhouse gas, exhibits spatio-temporal variability, challenging satellite observations. Existing methods like the Convective Cloud Differential (CCD) and Cloud Slicing Algorithms (CSA) are standard for Tropospheric Column Ozone (TCO) retrieval but are limited to the tropics (20°S-20°N). Notably, the CCD approach has proven successful with satellite sensors like Aura OMI, MetOp GOME-2, and Sentinel-5 Precursor TROPOMI.

In this study, we present the first successful application of CCD retrieval outside the tropical region. We introduce CHORA-CCD (Cloud Height Ozone Reference Algorithm-CCD) for retrieving TCO from TROPOMI in middle latitudes. It utilises a local cloud reference sector (CLCD, CHORA-CCD Local Cloud Decision) to determine the stratospheric (above cloud) column (ACCO) ozone.  This ACCO is later subtracted from the total column in clear-sky scenes to determine the TCO. The new approach minimises the impact of variances in stratospheric ozone.

An iterative approach is used to automatically select an optimal local cloud reference sector around each retrieval grid point, varying the radius from 60 to a maximum of 600 km around the grid box, for which a mean TCO is determined until a sufficient number of ground pixels with nearly fill cloud cover are found. Due to the prevalence of low-level clouds in middle latitudes, the estimation of TCO is constrained to the column up to a  reference altitude of 450 hPa.  An alternative method is introduced to directly estimate the ACCO down to 450 hPa by Theil-Sen regression in cases where the cloud-top heights in the local cloud sector are variable. The algorithm dynamically decides between CCD and Theil-Sen method for ACCO estimation by analysing the cloud characteristics. The CLCD algorithm is further refined by introducing a homogeneity criterion for total ozone to overcome inhomogeneities in stratospheric ozone.

Monthly averaged CLCD-TCOs have been determined over the middle latitudes (60◦S-60◦N) from TROPOMI for the time period from 2018 to 2022. The accuracy of the method was investigated by comparisons with spatially collocated SHADOZ/WOUDC/NDACC ozonesondes from thirty-one stations. The validation results reveal that TCO retrievals at 450 hPa using the CLCD algorithm exhibit good agreement with ozonesondes at most stations. At the tropical station Natal (5.4°S, 35.4°W), there is an outstanding agreement between CLCD and ozonesondes, showcasing minimal bias and scatter (0.3 ± 1.0 DU). Similarly, in the subtropics over Irene (25.9°S, 28.2°E), CLCD exhibits a significantly lower bias and scatter (0.0 ± 1.4 DU). Specifically, at one of the northernmost stations, Legionowo (52.4°N, 21°E), bias and dispersion are minimal (0.4 ± 2.2 DU). Across all stations, the maximum observed bias and dispersion are below around 5 DU and 4 DU, respectively. 

In this presentation, a detailed validation of the new local CCD retrievals will be given, underlining the advantage of using the local cloud reference sector in the middle latitudes, providing an important basis for subsequent systematic applications in current and future missions of geostationary satellites.

How to cite: Maratt Satheesan, S., Eichmann, K.-U., and Weber, M.: Extension of the S5P/TROPOMI CCD tropospheric ozone retrieval to middle latitudes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11316,, 2024.

Antonin Berthelot, Noel Baker, Philippe Demoulin, Ghislain Franssens, Didier Fussen, Pierre Gramme, Nina Mateshvili, Didier Pieroux, Sotiris Sotiriadis, and Emmanuel Dekemper

ALTIUS (Atmospheric Limb Tracker for the Investigation of the Upcoming Stratosphere) is an atmospheric limb mission being implemented in ESA's Earth Watch programme and planned for launch in 2026.

The instrument consists of three imagers: UV (250-355 nm), VIS (440-675 nm) and NIR (600-1040 nm) channels. Each channel is able to take a snapshot of the scene independently of the other two channels, at a desired wavelength and with the requested acquisition time. The agility of ALTIUS allows for series of high vertical resolution observations at wavelengths carefully chosen to retrieve the vertical profiles of species of interest.

ALTIUS will perform measurements in different geometries to maximize global coverage: observing limb-scattered solar light in the dayside, solar occultations at the terminator, and stellar, lunar, and planetary occultations in the nightside. The primary objective of the mission is to measure high-resolution stratospheric ozone concentration profiles. Secondary objectives are the retrieval of mesospheric ozone, stratospheric aerosols particle density and extinction coefficient, NO2, NO3, BrO, OClO, water vapor and temperature profiles.

The Level-2 retrievals use a Levenberg-Marquardt algorithm coupled to a Tikhonov regularization scheme to limit noise amplification during the inversion process. The type and strength of regularization has a direct effect on the retrieved profile vertical resolution. Therefore, a trade-off has to be found between noise removal amplitude and vertical resolution. A study on the different regularization constraint types is performed and the regularization strength is determined using the retrieval noise error in stellar occultation mode for O3 and NO2 density and aerosol extinction retrievals. The ability of Tikhonov regularization to remove the effects of scintillation on the retrieved profiles is discussed. Moreover, a re-processing of GOMOS data is performed to test the validity of our approach.

How to cite: Berthelot, A., Baker, N., Demoulin, P., Franssens, G., Fussen, D., Gramme, P., Mateshvili, N., Pieroux, D., Sotiriadis, S., and Dekemper, E.: Regularization scheme in ALTIUS retrieval algorithms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11354,, 2024.

Daniel Zacharias, Arthur Freitas, Agnès Borbon, Rita Ynoue, and Adalgiza Fornaro

BIOMASP+: Biogenic Volatile Organic Compounds in the Metropolitan Area of São Paulo (MASP) is a collaboration project among different French and Brazilian institutions to investigate the critical role of the biosphere-atmosphere interactions on urban pollution conditions and to evaluate how the biogenic volatile organic compounds (BVOC) affect the secondary pollutant formation.

Formaldehyde (HCHO) is the most abundant atmospheric carbonyl compound and a photochemical oxidation product of VOCs from several anthropogenic and natural sources [1]. Over São Paulo state (SP), HCHO arises from complex atmospheric interactions between a large urban area with 15 million of vehicles using four different fuel types, several industries, an extensive Atlantic Rainforest (3.9 104 km2), biomass burning and thousands of farms that cover 40% (2.5 105 km2) of the SP area [2]. The Metropolitan Area of São Paulo (MASP) is a highly polluted megacity [3], with concentrations that often exceed the World Health Organization guidelines, particularly for ozone and PM2.5, which are produced by photochemical reactions, such as the formaldehyde.

Vertical formaldehyde columns data (mol/m²) were obtained from the TROPOspheric Monitoring Instrument (TROPOMI) spectrometer onboard the Sentinel-5P satellite [2], and used in the WRF-CHEM model performance evaluation. Both, the long-term simulation and the Sentinel-5P data, covered the full 2022-year.

Satellite data confirmed the spatial distribution of HCHO simulated by WRF-CHEM, indicating MASP as the main formaldehyde hotspot in the state of São Paulo [2]. For the HCHO monthly averages, the normalized cross-correlation (i.e., spatial distribution) between model and satellite remains inside the range of: 0.3 < r < 0.6.

Using the satellite time series, it was possible to identify a bias in the HCHO simulated concentrations, that reached up to 80% in 1-year of simulation. This reduced the model's ozone production by up to 60% in the end of simulation. Comparing the simulation results with ozone data from air quality monitoring stations of the state of São Paulo [4], the linear correlation was within the range of 0.4 < r2 < 0.7, while the error was high (RMSE < 46.5).

A long-term (1-year) simulation with WRF-CHEM is quite challenging task [3], however, the TROPOMI data was crucial to identify modeling problems in areas with absence of air quality data, indicating possible adjustments and corrections in the emissions inventories.


[1]        Gao, S., et al., 2021, Atmospheric formaldehyde, glyoxal and their relations to ozone pollution under low- and high-NOx regimes in summertime Shanghai, China, Atmospheric Research,

[2]        Freitas & Fornaro, 2022, Atmospheric Formaldehyde Monitored by TROPOMI Satellite Instrument throughout 2020 over São Paulo State, Brazil, Remote Sensing,

[3]        Peralta, A., et al., 2023, Future Ozone Levels Responses to Changes in Meteorological Conditions under RCP 4.5 and RCP 8.5 Scenarios over São Paulo, Brazil., Atmosphere,

[4] CETESB <>



Keywords:  BIOMASP; Formaldehyde; TROPOMI; WRF-CHEM

How to cite: Zacharias, D., Freitas, A., Borbon, A., Ynoue, R., and Fornaro, A.: Comparison between Sentinel 5P and WRF-CHEM long-term simulations: An analysis based on TROPOMI HCHO data over São Paulo, Brazil within the BIOMASP+ project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13764,, 2024.

Marcus Hirtl, Barbara Scherllin-Pirscher, Marie Danielle Mulder, Christian Maurer, Maximilian Weissinger, Stefano Natali, Ramiro Marco Figuera, Clemens Rendl, Carl-Herbert Rokitansky, Fritz Zobl, Robert Marschallinger, Robert Faber, and Raimund Zopp

Aviation is a vulnerable infrastructure. This is not only true during economic crises such as the COVID-19 pandemic but also during natural hazards, especially airborne ones. Airborne hazards can be detected and observed by Earth Observation (EO) instruments. Most EO sensors that observe air pollutants fly on Sun-synchronous satellites. The strength of these satellites is global coverage and provision of high spatial resolution measurements. Their disadvantage is, that they do not observe high temporal variations of air pollutants. This is a severe limitation for the detection of natural hazards. One solution is to combine observations from Sun-synchronous (e.g., OMI, GOME2, TROPOMI, IASI, OMPS, AIRS) and geostationary (e.g., MSG-SEVIRI for Europe and Africa) instruments.

The Volcanic Ash Advisory Centers (VAACs) are responsible for predicting the dispersion of the volcanic plumes for the aviation sector. In addition, GeoSphere Austria supports the Austrian aviation authority (Austro Control) with information on volcanic ash and SO2 dispersion generated by the GeoSphere Austria emergency response Volcano Tool (GeoSphere Austria-VT). Since dispersion information needs to be available shortly after the eruption, VAACs and GeoSphere Austria forecasts are both based on rough estimates of source term parameters. The usage of near-real-time observations can significantly improve the source terms, and reduce the dispersion uncertainty. The GeoSphere Austria-VT is extended with a dynamic inverse modelling system that provides sequentially updated source terms using satellite data.

Apart from flying through volcanic plumes resulting possibly in a significant hazard, flying through regions with elevated air pollution levels has an impact on engine lifetime, maintenance costs, and fuel consumption. Here, the relevant factor is the cumulative air pollution intake over time. Additional costs associated with maintenance and repair are currently not considered in flight planning. Continuous monitoring, forecasting, and optimizing data integration of air pollutants into atmospheric models has thus two significant advantages: on the one hand, the obvious risk associated with flying through highly polluted air (including volcanic ash and SO2) is reduced, on the other hand, the impact on engine maintenance and fuel costs for airline operators and engine manufacturers is minimized. From the wide range of air pollutants, we will focus on aerosols (volcanic, dust and salt) and SO2, because these are the most relevant air pollutants for the aviation sector.

The aim is to implement a flexible, holistic system that is able to consider both hazardous and non-hazardous air pollution levels. The emphasis is on making extensive use of existing services (SACS, CAMS, VAACs) as well as air quality observations from satellites to extend and improve model applications (GeoSphere Austria-VT). To provide end-users with one comprehensive tool for the analysis and comparison of the air pollutants distribution from selected sources, these products will be available and visualized in one new data platform, exploiting a datacube-like approach to deal with the different spatial and temporal resolutions of the data.

How to cite: Hirtl, M., Scherllin-Pirscher, B., Mulder, M. D., Maurer, C., Weissinger, M., Natali, S., Figuera, R. M., Rendl, C., Rokitansky, C.-H., Zobl, F., Marschallinger, R., Faber, R., and Zopp, R.: Integrating EO and Copernicus Atmospheric services into emergency response tools to support flight planning Applications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14719,, 2024.

Nicolas Theys, Jonas Vlietinck, Huan Yu, Isabelle De Smedt, Lorenzo Fabris, Hugues Brenot, Jeroen van Gent, Sander Niemeijer, Fabian Romahn, Pascal Hedelt, Diego Loyola, and Michel Van Roozendael

Owing to its high spatial resolution, the TROPOspheric Monitoring Instrument (TROPOMI) launched in 2017 onboard the Sentinel-5 Precursor (S5P) platform provides important information on global volcanic and anthropogenic SO2 emissions, with an unprecedented level of details.

In a recent study (Theys et al., 2021), we proposed an approach called Covariance-Based Retrieval Algorithm (COBRA), different from the classical Differential Optical Absorption Spectroscopy (DOAS). Application of COBRA to TROPOMI SO2 column retrievals leads to a significant reduction of the retrieval noise and biases as compared to the TROPOMI operational (DOAS-based) SO2 product. COBRA even reveals new emission sources in long-term averaged SO2 maps.

In view of a future operational deployment (planned end 2024), the COBRA SO2 scheme is being implemented as part of the Copernicus S5-P Product Algorithm Laboratory (PAL). In this poster, we give an update of TROPOMI COBRA SO2 results. The latest developments of COBRA S5P-PAL v2 algorithm are presented and discussed. The pre-operational S5P-PAL environment enables a full reprocessing of TROPOMI data. For several examples, we illustrate the COBRA data set for the long-term monitoring of SO2 columns over both anthropogenic and volcanic scenes. Finally, possible future developments of COBRA are discussed.


Theys, N., Fioletov, V., Li, C., De Smedt, I., Lerot, C., McLinden, C., Krotkov, N., Griffin, D., Clarisse, L., Hedelt, P., Loyola, D., Wagner, T., Kumar, V., Innes, A., Ribas, R., Hendrick, F., Vlietinck, J., Brenot, H., and Van Roozendael, M.: A Sulfur Dioxide Covariance-Based Retrieval Algorithm (COBRA): application to TROPOMI reveals new emission sources, Atmos. Chem. Phys., 21, 16727–16744,, 2021.


How to cite: Theys, N., Vlietinck, J., Yu, H., De Smedt, I., Fabris, L., Brenot, H., van Gent, J., Niemeijer, S., Romahn, F., Hedelt, P., Loyola, D., and Van Roozendael, M.: Advanced retrieval of sulfur dioxide from TROPOMI using COBRA, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15017,, 2024.

Andrea Orfanoz-Cheuquelaf, Carlo Arosio, Alexei Rozanov, Mark Weber, and John Burrows

About 10% of the total amount of ozone resides in the troposphere, which acts as a potent greenhouse gas. Anthropogenic emissions and biomass burning are the main sources of ozone in the troposphere, and overexposure to this pollutant causes health problems and damages vegetation.

A combination of space-borne limb and nadir measurements in the UV-visible spectral range (so-called limb-nadir matching, LNM) provides valuable information on tropospheric ozone. This study uses data from the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) (2002-2012) and Ozone Mapping and Profiler Suite on board of Suomi National Polar-Orbiting Partnership (OMPS/NPP, since 2012). Both instruments observe the atmosphere in both limb and nadir geometry. Tropospheric ozone columns are retrieved globally by subtracting the stratospheric ozone column calculated from limb observations from the total ozone column derived from the nadir measurements.

Tropospheric ozone retrievals use different upper altitude limits to calculate the tropospheric ozone column. In the case of the LNM technique, the upper limit is defined by the thermal and/or dynamical tropopause. The Convective Clouds Differential technique (CCD) calculates the tropospheric ozone column up to 270 hPa. Phase II of the Tropospheric Ozone Assessment Report (TOAR-II) uses different pressure levels for different latitudes as an upper limit for the tropospheric column.

After updating and improving the SCIAMACHY-LNM and the OMPS/NPP-LNM datasets, we obtained a long-term dataset of tropospheric ozone (2002-2023) by merging them. Here, we present this new long-term LNM tropospheric ozone column dataset, which has been converted to the different definitions of column heights as prescribed in TOAR II. The datasets are validated using ozonesondes, and the results for the different column definitions are evaluated and discussed.

How to cite: Orfanoz-Cheuquelaf, A., Arosio, C., Rozanov, A., Weber, M., and Burrows, J.: Long-term tropospheric ozone from SCIAMACHY+OMPS and effects of the upper limit definition of the column, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16562,, 2024.

Gerrit de Leeuw, Ouyang Liu, Zhengqiang Li, Yangyan Lin, Cheng Fan, Ying Zhang, Kaitao Li, Peng Zhang, Yuanyuan Wei, Tianzeng Chen, and Jiantao Dong

A Pandora spectrometer has been installed on the roof of the laboratory building of the Aerospace Information Research Institute of the Chinese Academy of Sciences in the Olympic Park, Beijing, China, in August 2021. The concentrations of trace gases (including NO2, HCHO, O3) measured with Pandora are made available through the open-access Pandora data base ( The Beijing-RADI Pandora is included in the data suite which is routinely used for TROPOMI S5P validation. The use of Pandora total and tropospheric NO2 VCDs for validation of collocated TROPOMI data, resampled to 100×100 m2, shows that although on average the TROPOMI VCDs are slightly lower, they are well within the expected error for TROPOMI. The location of the Pandora instrument within a sub-orbital TROPOMI pixel of 3.5×5.5 km2 may result in an error in the TROPOMI-derived tropospheric NO2 VCD between 0.223 and 0.282, i.e., between 1.7% and 2%. In addition, the data also show that the Pandora observations at the Beijing-RADI site are representative for an area with a radius of 10 km.

The Pandora total and tropospheric NO2 vertical column densities (VCDs) and surface concentrations collected during the first year of operation show that NO2 concentrations were high in the winter and low in the summer, with diurnal cycle where the concentrations reach a minimum during day time. The concentrations were significantly lower during the 2022 Winter Olympics in Beijing, showing the effectiveness of the emission control measures during that period. The Pandora observations show that during northerly winds clean air is transported to Beijing with low NO2 concentrations, whereas during southerly winds pollution from surrounding areas is transported to Beijing and NO2 concentrations are high. The contribution of tropospheric NO2 to the total NO2 VCD varies significantly on daily to seasonal time scales, i.e., monthly averages vary between 50% and 60% in the winter and between 60% and 70% in the spring and autumn. The comparison of Pandora-measured surface concentrations with collocated in situ measurements using a Thermo Scientific 42i-TL Analyzer shows that the Pandora data are low and that the relationship between Pandora-derived surface concentrations and in situ measurements are different for low and high NO2 concentrations. Explanations for these differences are offered in terms of measurement techniques and physical (transport) phenomena.

How to cite: de Leeuw, G., Liu, O., Li, Z., Lin, Y., Fan, C., Zhang, Y., Li, K., Zhang, P., Wei, Y., Chen, T., and Dong, J.: Interpretation of Pandora NO2 measurements over Beijing and application to satellite validation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17891,, 2024.

Yuxiang Zhang

Tropospheric NO2, one of the major atmospheric pollutants, is harmful to human health and plays an important role in atmospheric chemistry. Tropospheric NO2 concentration is controlled by anthropogenic emission and meteorological conditions, such as solar radiation and humidity. In early 2020, unprecedented lockdowns and travel bans were implemented in China to fight COVID-19, leading to a large decrease of NO2 compared with preceding years. To isolate the effects of anthropogenic emission and weather, we applied a linear regression model between satellite observed NO2 column density and meteorological variables. Compared with 2017, it is found that atmospheric NO2 in 2020 changed -37.8 ± 16.3 %, with the contribution of weather +8.1 ± 14.2 % and anthropogenic emission -49.3 ± 23.5 %. Similar results were also found in 2018 and 2019, revealing that the effect of reduced emission on atmospheric NO2 is counteracted by the weather, and is actually larger than the observation. The simulations by GEOS-Chem model also supported the results in typical regions. The reduction of NO2 induced by anthropogenic emission can be well explained by human mobility, showing significantly negative correlations to migration indices provided by Baidu Location-Based-Service, particularly that inside the city. The intra-city migration index can explain 40.4 ± 17.7 % variance of the emission-induced reduction of NO2 in 29 megacities, each of which has a population of over 8 million in China.

How to cite: Zhang, Y.: Tropospheric NO2 in China during the COVID-19 lock-down is largely decreased due to the controlled human mobility, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17976,, 2024.

Yathin Kudupaje Laxmana, Thomas Lauvaux, Philippe Ciais, Pramod Kumar, Ioannis Cheliotis, Jinghui Lian, and Anthony Rey-Pommier

Quantification of NO2 from different sectors of economic activity remains critical to monitor air pollutants with the rapid development of infrastructures and the rapid industrialization of emerging economies. This study aims to estimate NO2 emissions using satellite NO2 measurements from TROPOMI from different activity sectors over northern Egypt using a full-chemistry atmospheric transport model (WRF-Chem, including aerosol chemistry) and a non-linear Bayesian method. Our top-down approach was carried out for two months, January and July 2022, to analyse the seasonal variations in NO2 emissions over the studied region. The major source of uncertainties in our top-down emission estimates is due to missing sources in the prior emissions (fossil fuel inventory),  lacking more frequent updates and sub-monthly information. We also explore other sources of errors, such as the level of uncertainty used for calculating error covariance factors, the estimation of biogenic emissions, the selection of a quality assurance filter of TROPOMI NO2 and the use of regularization parameters. Non-linearities are included in our optimization algorithm by performing sensitivity experiments with the direct chemistry model (error propagation) to establish daily relationships between NO2 fluxes and concentrations. Our Bayesian inversion produces optimized values over sub-regions of Egypt and for specific sectors. We defined several subregions and assessed the regional NO2 emissions. The total estimated NO2 emissions from the studied region are about 45 Kt for the month of January 2022 and 32 Kt for the month of July 2022. The results were compared to a previous study using the flux-divergence method, showing a fair agreement for the month of winter (R2=0.67) but disagree in terms of magnitude during summer. We discuss the potential causes for the observed mismatch, which is possibly due to the extreme climate of the region, the availability of satellite observations, and large seasonal variations in the lifetime of NO2.

How to cite: Kudupaje Laxmana, Y., Lauvaux, T., Ciais, P., Kumar, P., Cheliotis, I., Lian, J., and Rey-Pommier, A.: Monitoring of NO2 emissions from space using an aerosol chemistry transport model and a non-linear optimization system, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19024,, 2024.

Davide De Santis, Sarathchandrakumar T. Sasidharan, Marco Di Giacomo, Gianmarco Bencivenni, Fabio Del Frate, Gabriele Curci, Ana Carolina Amarillo, Francesca Barnaba, Luca Di Liberto, Ferdinando Pasqualini, Cristiana Bassani, Silvia Scifoni, Stefano Casadio, Alessandra Cofano, Massimo Cardaci, and Giorgio Licciardi

The challenge of air pollution and its impact on human health is a significant concern in contemporary society. The PRIMARY (PRIsma for Monitoring AiR quality) research project aims to leverage the capabilities of the Italian Space Agency's PRISMA (PRecursore IperSpettrale della Missione Applicativa) mission to enhance air quality monitoring, particularly in urban areas. The project seeks to utilize PRISMA's hyperspectral data for detailed qualitative and quantitative insights into atmospheric aerosol content and composition in urban environments, crucial for understanding the environmental and health impacts of particulate matter. PRISMA's decametric spatial resolution and the project's use of artificial intelligence address limitations in spatial resolution and the complexity of the inverse problem in satellite-based characterization of particulate matter.

In the context of the PRIMARY project, which deals with high-dimensional hyperspectral data, feature extraction before inversion modeling presents challenges, especially when employing machine learning techniques like neural networks (NNs). Dimensionality reduction addresses this challenge by using feature extraction. Comparative evaluation on a PRISMA dataset for Rome showed variable performance between PCA and NN models in compressing and reconstructing the original vector. Additionally, a synthetic dataset was generated to train the algorithm for atmospheric aerosol composition recognition, relying on a sufficiently large number of aerosol profile examples. The Copernicus Atmosphere Monitoring (CAMS) service, specifically its global atmospheric composition forecast product, was chosen as the primary data source. The FlexAOD code, a post-processing tool, was adapted to read CAMS data and obtain aerosol optical properties for input into LibRadtran, a radiative transfer model, used to generate PRISMA-like synthetic data. The resulting dataset, obtained through automated processes, serves as training data for neural networks. To provide validation for the PRIMARY products, the project planned dedicated measurement campaigns in Rome (autumn 2022) and Milan (from winter to summer 2023).


The PRIMARY project is co-funded by the Italian Space Agency (ASI – “Tor Vergata” University of Rome Agreement n. 2022-3 U.0); the project is part of the ASI’s program “PRISMA Scienza”.

How to cite: De Santis, D., Sasidharan, S. T., Di Giacomo, M., Bencivenni, G., Del Frate, F., Curci, G., Amarillo, A. C., Barnaba, F., Di Liberto, L., Pasqualini, F., Bassani, C., Scifoni, S., Casadio, S., Cofano, A., Cardaci, M., and Licciardi, G.: AI and physical models for air quality monitoring at urban scale with PRISMA hyperspectral data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19760,, 2024.

Isabelle De Smedt, Huan Yu, Nicolas Theys, Klaus-Peter Heue, Steven Compernolle, Gaia Pinardi, Pascal Hedelt, Gijsbert Tilstra, Thomas Danckaert, Corinne Vigouroux, Bavo Langerock, Diego Loyola, Andreas Richter, Folkert Boersma, and Michel Van Roozendael

The ESA Climate Change Initiative (CCI) Ozone and Aerosols Precursors project is developing long-term climate data records (CDRs) of the Global Climate Observing System (GCOS) Precursors for Aerosol and Ozone Essential Climate Variables. These precursors include short-lived atmospheric trace gases such as formaldehyde (HCHO), glyoxal (CHOCHO), nitrogen dioxide (NO2), sulphur dioxide (SO2), carbon monoxide (CO), and ammonia (NH3). The project aims to create consistent and harmonized CDRs from multiple satellite missions, including GOME, SCIAMACHY, GOME-2, OMI, TROPOMI, IASI, and MOPITT.

This work presents selected findings of a round robin exercise conducted for UV-VIS retrievals. We focus on two key factors that influence HCHO air mass factor determination: the surface albedo climatology and the model a priori profiles. The impact of these factors on the HCHO vertical columns is evaluated by comparing the use of recent auxiliary datasets. Results are presented for TROPOMI HCHO columns and compared to the operational product.

The recent reprocessing of TROPOMI Level 1 data has enabled the development of new albedo climatologies in the UV, offering a finer spatial resolution than the previously used OMI albedo climatology. Additionally, we evaluate the use of a priori vertical profiles from the CAMS reanalysis dataset (spanning the 2003-2022 period) instead of the current TM5-MP profiles used in the TROPOMI operational product. We assess the impact of these alternative datasets on the TROPOMI HCHO vertical columns and on their validation towards ground-based data.

The generation of the ESA CCI HCHO CDR will be based on these findings. This comprehensive assessment not only contributes to the ongoing improvement of TROPOMI data quality but also provides deeper insights into the factors influencing HCHO vertical columns.

How to cite: De Smedt, I., Yu, H., Theys, N., Heue, K.-P., Compernolle, S., Pinardi, G., Hedelt, P., Tilstra, G., Danckaert, T., Vigouroux, C., Langerock, B., Loyola, D., Richter, A., Boersma, F., and Van Roozendael, M.: Assessment of TROPOMI HCHO Vertical Columns: evaluating the use of CAMS vertical profiles and new TROPOMI surface albedo climatologies for air mass factor determination, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20191,, 2024.

Rainer Volkamer, Christopher Lee, Rebecca Mesburis, Catherine Silver, Mago Reza, Alan Brewer, Steven Brown, Brian McDonald, Kristen Zuraski, and Sunil Baidar

The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite was launched in April 2023 by NASA and has been measuring tropospheric trace gases with hourly time resolution over North America since August 2023. The geostationary orbit of TEMPO poses advantages and also some new challenges to satellite validation efforts (e.g., due to changes in geometry, stratospheric correction, and the spatial scales of sampling) that remain understudied. Overlapping with TEMPO’s early measurement phase, the University of Colorado Airborne Multi-Axis Differential Optical Absorption Spectroscopy (CU AMAX-DOAS) instrument was deployed to probe tropospheric NO2 and other trace gas columns during research flights over New York City, NY conducted as part of the Coastal Urban Plume Dynamics Study (CUPiDS) from July 15 to August 15, 2023. CU AMAX-DOAS is co-deployed with a NOAA Doppler lidar, two 4-channel radiometers (surface albedo), and in situ measurements onboard the NOAA Twin Otter aircraft, with the objectives to better understand emissions and meteorology as drivers for air quality in coastal Metropolitan areas. This presentation focuses on the inter-comparison of tropospheric NO2 trace gas columns from TEMPO and AMAX-DOAS remote sensing measurements. 

How to cite: Volkamer, R., Lee, C., Mesburis, R., Silver, C., Reza, M., Brewer, A., Brown, S., McDonald, B., Zuraski, K., and Baidar, S.: Evaluating TEMPO NO2 over the New York City Metropolitan Area during CUPiDS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20818,, 2024.

Rebekah Horner, Eloise Marais, and Nana Wei

Lightning is the dominant source of nitrogen oxides (NOx) in the free troposphere. Yet, its representation in models is highly parameterised, limiting our ability to determine past and future changes in lightning NOx and causing errors in model representation of tropospheric ozone and NOx. Models such as GEOS-Chem use fixed lightning NOx production rates constrained with historic satellite instrument observations of ozone. A new approach is to model NOx production per flash (mol N fl-1) using lightning energy dependent NOx yields and lightning flash radiant energy data from the space-based lightning imaging sensor (LIS) aboard both the Tropical Rainfall Measuring Mission (TRMM) satellite and the International Space Station (ISS). This updated approach is then used in GEOS-Chem to compute total lightning NOx yields through the Harmonized Emissions Component (HEMCO), rather than using fixed values. The updated annual lightning NOx emissions total 6.5 Tg N, similar to the original parameterised representation (5.8 Tg N), but with much greater variability in NOx production rates. The original implementation uses 260 mol N fl-1 everywhere except the northern extratropics that are at 500 mol fl-1. In the updated implementation, values range from 27 to 632 mol N fl-1 over the ocean and from 66 to 482 mol N fl-1 over land. Greater values over the ocean are due to oft-reported much more energetic maritime lightning. To test the effect on tropospheric ozone and NOx, we are currently comparing seasonal mean GEOS-Chem and TROPOMI-derived vertical profiles of ozone and NO2. The TROPOMI-derived values, obtained by cloud-slicing partial columns over optically thick clouds, we have previously evaluated to be consistent with NASA DC-8 aircraft measurements in the free troposphere for cloud-sliced NO2 (differences < 20 pptv) and the global ozonesonde network for cloud-sliced ozone across the whole troposphere (differences < 35 ppbv). This offers the means to assess the representation of lightning NOx and better understand its influence on tropospheric NOx and ozone.

How to cite: Horner, R., Marais, E., and Wei, N.: Improved lightning NOx emission inventory evaluated with vertical profiles of NO2 and ozone obtained by cloud-slicing TROPOMI  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8441,, 2024.

Identifying and accounting for the Coriolis effect in satellite NO2 observations and emission estimates
Daniel Potts, Roger Timmis, Emma Ferranti, and Joshua Vande Hey
Selviga Sinnathamby, Sarah Safieddine, Camille Viatte, Juliette Hadji-Lazaro, Maya George, PIerre Coheur, Lieven Clarisse, Martin Van Damme, and Cathy Clerbaux

South Asia, with its high population density supported by thriving industrial and agricultural sectors, is one of the most polluted region in the world. In early November 2023, the region along the Himalayas, the Indo-Gangetic Plain (IGP), experienced a severe air pollution episode that affected visibility over several thousand kilometers and impacted millions of inhabitants.

Here we use a variety of measurements and datasets to attempt to untangle the reasons behind the formation and the buildup of this pollution episode. Using IASI (Infrared Atmospheric Sounding Interferometer) measurements, embarked on board of the Metop satellites, we find exceptionnally high concentrations of carbon monoxide (CO) and ammonia (NH3) in the Northwestern states of IGP. Fire satellite measurements from MODIS (Terra and Aqua) and VIIRS (Suomi-NPP and NOAA-20) show that CO is mainly emitted from agricultural waste burning, prevalent at the post-monsoon season. NH3 primarily emanated from extensive applications of nitrogenous fertilizers, as well as fires, contributing to the formation of fine particulate matter (PM2.5) in the region and degrading the air quality as seen by local air quality stations. ERA5 reanalysis unveiled that these high concentrations of pollutants and their buildup was favored by meteorological conditions that resulted in air mass stagnation, facilitating the accumulation of pollutants in the region.

This study builds a framework to demonstrate the potential of using satellite instruments data, in situ measurements, and reanalysis combined to understand the formation and the progression of air pollution episodes in South Asia.

How to cite: Sinnathamby, S., Safieddine, S., Viatte, C., Hadji-Lazaro, J., George, M., Coheur, P., Clarisse, L., Van Damme, M., and Clerbaux, C.: The November 2023 severe pollution episode in Pakistan and Northern India , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10413,, 2024.

Karol Przeździecki, Joanna Strużewska, Jacek Kamiński, Grzegorz Jeleniewicz, Damian Mochocki, and Marcin Kawka

Copernicus provides a wide variety of services covering different topics, starting from Atmosphere through Marine, Land, Climate Change, Security and Emergency.

Satellite observations on atmospheric composition, complementary to Copernicus Atmosphere Monitoring Service (CAMS), become increasingly available. Unfortunately, analysis or even opening of satellite data in their native formats prove to be challenging in communities other than scientific.

Functionalities, data products, and analysis provided to users on the CAMS website are mainly at the global and European scales. It has been recognized that usage of those services and data they provided by Member States are rather unsatisfactory. Therefore, ECWF prepared CAMS National Collaboration Programmes for member states to improve the uptake of CAMS products at the national, regional and local levels, responding to regulatory needs coming from public administration, NGO's and other interested parties. Institute of Environmental Protection – National Research Institute is responsible for the provision and development of the CAMS National Collaboration Programme for Poland.

We will present the usage of prepared averaged products derived from Sentinel 5P AER AI, Sentinel 5P NO2, and S5P HCHO data in investigating transport episodes connected with wildfires or desert dust over the Polish region. We have investigated data from 2019 to 2023 for both RPRO and OFFL Sentinel 5P products.

We will also discuss the potential usage of other products being tailored and developed during the CAMS NCP Poland project, which have been indicated during the preliminary communication phase via survey  and discussion on 1-st User and stakeholder meeting. The study's outcome would also be important for the HE CAMEO project, where we investigate potential benefits from the assimilation of satellite data to the regional models.

How to cite: Przeździecki, K., Strużewska, J., Kamiński, J., Jeleniewicz, G., Mochocki, D., and Kawka, M.: Enhancing Environmental Monitoring in Poland: Leveraging Sentinel Satellite Data through the CAMS National Collaboration Programme, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17309,, 2024.