Henk Eskes’s research while affiliated with Koninklijk Nederlands Meteorologisch Instituut and other places

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Publications (166)


Comparison of NO2 vertical column densities over the Netherlands on 5 July 2018, derived from synthetic and actual TROPOMI observations. (a) Synthetic observations at native LOTOS-EUROS resolution (2×2km2). (b) Synthetic observations spatiotemporally interpolated into the TROPOMI grid and excluding the pixels where TROPOMI observations do not satisfy a quality assurance value over 0.75. (c) TROPOMI observations using the default TM5-MP a priori profile shape. (d) TROPOMI observations using a high-resolution a priori profile shape derived from the LOTOS-EUROS simulation.
Schematic representation of the evaluation system designed to assess the accuracy of the NOx emissions derived using the flux divergence approach.
Comparison between the original and convoluted NOx model-ingested emissions and FDA-derived emissions for June, July, and August (JJA) at 13:30 LT using configuration ID06. (a) Original model-ingested NOx. (b, e) FDA-derived NOx. (c) Difference between the FDA-derived NOx and the original ingested NOx. (d) Convoluted model-ingested NOx. (f) Difference between the FDA-derived NOx and the convoluted ingested NOx.
Taylor diagram summarizing the FDA performance for the seven sensitivity tests in Table with IDs 01 to 07 using (a) the original model-ingested emissions and (b) convoluted model-ingested emissions as a reference.
Mean NOx emissions and divergence for June, July, and August (JJA) at 13:30 LT derived from the synthetic dataset at LOTOS-EUROS native resolution using configuration ID06. (a) Convoluted NOx emissions ingested into LOTOS-EUROS. (b) FDA-derived NOx emissions. (c)NOx flux divergence. (d) Difference in NOx emissions between the FDA-derived dataset and the convoluted model-ingested emissions.

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Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
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February 2025

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Henk Eskes

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The flux divergence approach (FDA) is a popular technique for deriving NOx emission estimates from tropospheric NO2 columns measured by the TROPOspheric Monitoring Instrument (TROPOMI) satellite sensor. An attractive aspect of the FDA is that the method simplifies three-dimensional atmospheric chemistry and transport processes into a two-dimensional (longitude–latitude) steady-state continuity equation for columns that balances local NOx emissions with the net outflow and chemical loss of NOx. Here we test the capability of the FDA to reproduce known NOx emissions from synthetic NO2 column retrievals generated with the LOTOS-EUROS chemistry transport model over the Netherlands at high spatial resolution of about 2×2km during summer. Our results show that the FDA captures the magnitude and spatial distribution of the NOx emissions to high accuracy (absolute bias <9 %), provided that the observations represent the NO2 column in the boundary layer, that wind speed and direction are representative for the boundary layer (PBL) column, and that the high-resolution spatiotemporal variability of the NO2 lifetimes and NOx:NO2 ratio is accounted for in the inversion instead of using single fixed values. The FDA systematically overestimates NOx emissions by 15 %–60 % when using tropospheric NO2 columns as the driving observation, while using PBL NO2 columns largely overcomes this systematic error. This merely reflects the fact that the local balance between emissions and sinks of NOx occurs in the boundary layer, which is decoupled from the NO2 in the free troposphere. Based on the recommendations from this sensitivity test, we then applied the FDA using observations of NO2 columns from TROPOMI, corrected for contributions from free-tropospheric NO2, between 1 June and 31 August 2018. The NOx emissions derived from the default TROPOMI retrievals are biased low over cities and industrialized areas. However, when the coarse 1×1° TM5-MP NO2 profile used in the retrieval is replaced by the high-resolution profile of LOTOS-EUROS, the TROPOMI NOx emissions are enhanced by 22 % and are in better agreement with the inventory for the Netherlands. This emphasizes the importance of using realistic high-resolution a priori NO2 profile shapes in the TROPOMI retrieval. We conclude that accurate quantitative NOx emissions estimates are possible with the FDA, but they require sophisticated, fine-scale corrections for both the NO2 observations driving the method and the estimates of the NO2 chemical lifetime and NOx:NO2 ratio. This information can be obtained from high-resolution chemistry transport model simulations at the expense of the simplicity and applicability of the FDA.

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Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation

January 2025

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12 Reads

Satellite observations of tropospheric trace gases and aerosols are evolving rapidly. Recently launched instruments provide increasingly higher spatial resolutions, with footprint diameters in the range of 2–8 km and with daily global coverage for polar orbiting satellites or hourly observations from geostationary orbits. Often the modelling system has a lower spatial resolution than the satellites used, with a model grid size in the range of 10–100 km. When the resolution mismatch is not properly bridged, the final analysis based on the satellite data may be degraded. Superobservations are averages of individual observations matching the model's resolution and are functional to reduce the data load on the assimilation system. In this paper, we discuss the construction of superobservations, their kernels, and uncertainty estimates. The methodology is applied to nitrogen dioxide tropospheric column measurements of the TROPOspheric Monitoring Instrument (TROPOMI) instrument on the Sentinel-5P satellite. In particular, the construction of realistic uncertainties for the superobservations is non-trivial and crucial to obtaining close-to-optimal data assimilation results. We present a detailed methodology to account for the representation error when satellite observations are missing due to, e.g., cloudiness. Furthermore, we account for systematic errors in the retrievals leading to error correlations between nearby individual observations contributing to one superobservation. Correlation information is typically missing from the retrieval products, where an error estimate is provided for individual observations. The various contributions to the uncertainty are analysed from the spectral fitting and the estimate of the stratospheric contribution to the column and the air mass factor for which we find a typical correlation length of 32 km. The method is applied to TROPOMI data but can be generalized to other trace gases such as HCHO, CO, and SO2 and other instruments such as the Ozone Monitoring Instrument (OMI), the Geostationary Environment Monitoring Spectrometer (GEMS), and the Tropospheric Emissions: Monitoring of POllution (TEMPO) instrument. The superobservations and uncertainties are tested in the Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation ensemble Kalman filter system. These are shown to improve forecasts compared to thinning or compared to assuming fully correlated or uncorrelated uncertainties within the superobservation. The use of realistic superobservations within model comparisons and data assimilation in this way aids the quantification of air pollution distributions, emissions, and their impact on climate.


Global seasonal urban, industrial, and background NO2 estimated from TROPOMI satellite observations

January 2025

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24 Reads

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 NOx emissions for 261 major cities worldwide. The used algorithm isolated three components in tropospheric NO2 data – background NO2, NO2 from urban sources, and NO2 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. The largest per capita emissions were found in the Middle East, and the smallest were in India and southern Africa. The largest background component was observed over China and parts of Europe, while the smallest was over South America, Australia, and New Zealand. 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. The background component typically does not show any significant differences between workdays and weekends, suggesting that background NO2 has a substantially longer lifetime compared to that in the urban and industrial plumes.


Challenges and opportunities offered by geostationary space observations for air quality research and emission monitoring

January 2025

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90 Reads

Bulletin of the American Meteorological Society

Space-borne remote sensing of atmospheric chemical constituents is crucial for monitoring and better understanding global and regional air quality. Since the 1990s, the continuous development of instruments onboard low-Earth orbit (LEO) satellites has led to major advances in air quality research by providing daily global measurements of atmospheric chemical species. The next generation of atmospheric composition satellites measures from the geostationary Earth orbit (GEO) with hourly temporal resolution, allowing the observation of diurnal variations of air pollutants. The first two instruments of the GEO constellation coordinated by the Committee on Earth Observation Satellites (CEOS), the Geostationary Environment Monitoring Spectrometer (GEMS) for Asia and the Tropospheric Emissions: Monitoring of Pollution (TEMPO) for North America, were successfully launched in 2020 and 2023, respectively. The European component, Sentinel-4, is planned for launch in 2025. This work provides an overview of satellite missions for atmospheric composition monitoring and the state of the science in air quality research. We cover recent advances in retrieval algorithms, the modeling of emissions and atmospheric chemistry, data assimilation, and the application of machine learning based on satellite data. We discuss the challenges and opportunities in air quality research in the era of GEO satellites, and provide recommendations on research priorities for the near future.


Copernicus Atmosphere Monitoring Service – Regional Air Quality Production System v1.0

December 2024

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153 Reads

The Copernicus Atmosphere Monitoring Service (CAMS) delivers a range of full, free and open products in relation to atmospheric composition at global and regional scales. The CAMS Regional Service produces daily forecasts, analyses, and reanalyses of air quality in Europe. This Service relies on a distributed modelling production by eleven teams in ten European countries: CHIMERE (France), DEHM (Denmark), EMEP (Norway), EURAD-IM (Germany), GEM-AQ (Poland), LOTOS-EUROS (The Netherlands), MATCH (Sweden), MINNI (Italy), MOCAGE (France), MONARCH (Spain), SILAM (Finland). The project management and coordination of the service is devoted to a Centralised Regional Production Unit. Each model produces every day 24 h analyses for the previous day and 97 h forecasts for 19 chemical species over a spatial domain at 0.1x01. degree resolution (approximately 10 km x 10 km) with 420 points in latitude and 700 in longitude and 10 vertical levels. Six pollen species are also delivered for the surface forecasts. The eleven individual models are then combined into an ENSEMBLE median. In total, more than 82 billion data points are made available for public use on a daily basis. The design of the system follows clear technical requirements in terms of consistency in the model setup and forcing fields (meteorology, surface anthropogenic emission fluxes, and chemical boundary conditions). But it also benefits from a diversity of in the description of atmospheric processes through the design of the eleven European Chemistry Transport Models (CTM) involved. The present article aims to provide a comprehensive technical documentation, both for the setup as well as for the diversity of CTM involved in the Service. We also include an overview of the main output products, their public dissemination and the related evaluation and quality control strategy.


European Soil NOx Emissions Derived From Satellite NO2 Observations

December 2024

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108 Reads

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2 Citations

We introduce an innovative method to distinguish soil nitrogen oxides (NOx = NO + NO2) emissions from satellite‐based total NOx emissions. To evaluate the approach, we compare the deviation between the tropospheric NO2 concentration observed by satellite and two atmospheric composition model simulations driven by the newly estimated soil NOx emissions and the Copernicus Atmosphere Monitoring Service (CAMS) inventory. The estimated average soil NOx emissions in Europe are 1.7 kg N ha⁻¹ yr⁻¹ in 2019, and the annual soil NOx emissions are approximately 1.7 times larger than that of the CAMS inventory. The discrepancy originates mainly from the forests, which would mean that the soil NOx emissions over forest areas in Europe are currently underestimated by the CAMS inventory. The model evaluation indicates that the simulations driven by DECSO‐soil emissions performed significantly better than using CAMS‐soil. Overall, the simulated RMSE% of DECSO‐soil is lower than that of CAMS‐soil, approximately 6% lower in spring and 2% lower in autumn. Our method can easily be extended to other regions in the world despite having monthly variations that are very different from those in Europe.


Decrease of the European NO x anthropogenic emissions between 2005 and 2019 as seen from the OMI and TROPOMI NO 2 satellite observations

December 2024

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30 Reads

There are great expectations about the detection and the quantification of NOx emissions using NO2 tropospheric columns from satellite observations and inverse systems. This study assesses the potential of the OMI-QA4ECV and TROPOMI satellite observations to improve the knowledge on European NOx emissions at the regional scale and to inform about the spatio-temporal variability of NOx anthropogenic emissions from 2005 to 2019, at the resolution of 0.5° over Europe. Starting from European emission estimates from the TNO-GHGco-v3 inventory for the year 2005, regional inversions using the Community Inversion Framework coupled to the CHIMERE chemistry-transport model and assimilating satellite NO2 tropospheric columns from OMI and TROPOMI have been performed to estimate the European annual and seasonal budgets for the year 2019. Both the OMI and TROPOMI inversions show decreases in European NOx anthropogenic emission budgets between 2005 and 2019 but the magnitude of the reductions differs with OMI and TROPOMI data (-16 % and -45 %, respectively). A TROPOMI in-version giving more weight to the satellite data becomes consistent with the independent TNO-GHGco-v3 inventory for the year 2019, with annual budgets for EU-27+UK showing absolute relative difference of only 4 %. These TROPOMI inversions are therefore in agreement with the magnitude of the decline in NOx emissions declared by countries, when aggregated at the European scale. However, our results —with OMI and TROPOMI data leading to different magnitudes of corrections on NOx anthropogenic emissions—suggest that more observational constraints would be required to sharpen the European emission estimates.


Ammonia emission estimates using CrIS satellite observations over Europe

September 2024

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106 Reads

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1 Citation

Over the past century, ammonia (NH3) emissions have increased with the growth of livestock and fertilizer usage. The abundant NH3 emissions lead to secondary fine particulate matter (PM2.5) pollution, climate change, and a reduction in biodiversity, and they affect human health. Up-to-date and spatially and temporally resolved information on NH3 emissions is essential to better quantify their impact. In this study we applied the existing Daily Emissions Constrained by Satellite Observations (DECSO) algorithm to NH3 observations from the Cross-track Infrared Sounder (CrIS) to estimate NH3 emissions. Because NH3 in the atmosphere is influenced by nitrogen oxides (NOx), we implemented DECSO to estimate NOx and NH3 emissions simultaneously. The emissions are derived over Europe for 2020 on a spatial resolution of 0.2°×0.2° using daily observations from both CrIS and the TROPOspheric Monitoring Instrument (TROPOMI; on the Sentinel-5 Precursor (S5P) satellite). Due to the limited number of daily satellite observations of NH3, monthly emissions of NH3 are reported. The total NH3 emissions derived from observations are about 8 Tgyr-1, with a precision of about 5 %–17 % per grid cell per year over the European domain (35–55° N, 10° W–30° E). The comparison of the satellite-derived NH3 emissions from DECSO with independent bottom-up inventories and in situ observations indicates a consistency in terms of magnitude on the country totals, with the results also being comparable regarding the temporal and spatial distributions. The validation of DECSO over Europe implies that we can use DECSO to quickly derive fairly accurate monthly emissions of NH3 over regions with limited local information on NH3 emissions.


a–d, TROPOMI NO2 total GCD (a) and water vapour (b) fit coefficients (b) over the lake Siling Co with quality flag >0.75 (high quality, cloud-free data), and fit residuals of the two pixels marked in a and b over land (c) and water (d). Pixel centre longitude and latitude are 88.458° E, 31.904° N (land) and 89.095° E, 31.811° N (water). Data are taken from TROPOMI orbit 08511 of 5 June 2019. Standard S5P/TROPOMI level-2 NO2 (L2__NO2___) data are freely available via the Copernicus Data Space Ecosystem (CDSE, https://dataspace.copernicus.eu/). Detailed analysis data, such as fit residuals, are not available in the regular TROPOMI NO2 data files but are available upon request (see Data availability statement).
a, Map of the water-vapour fit coefficient from the TROPOMI NO2 retrieval for several lakes in Asia. b, Fit residuals for land pixels (left column) near and water pixels (right column) over Lake Nam in Tibet (top row) and Lake Issyk Kul in Kyrgyzstan (bottom row), which can be compared to Fig. 1c,d for Lake Siling. Data are taken from TROPOMI orbit 08511 of 5 June 2019. Standard S5P/TROPOMI level-2 NO2 (L2__NO2___) data are freely available via the CDSE (https://dataspace.copernicus.eu/). Detailed analysis data, such as fit residuals, are not available in the regular TROPOMI NO2 data files but are available upon request (see Data availability statement).
NO2 satellite retrievals biased by absorption in water

September 2024

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114 Reads

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1 Citation

Localized tropospheric nitrogen oxides (NOx = NO + NO2) are mostly formed from emission sources, such as large cities1, mineral mining sites2, busy transportation routes3, fuel delivery infrastructure4 and wildfires5. Kong et al.6 recently reported anomalous tropospheric NO2 columns from spaceborne remote sensing observations of the TROPOspheric Monitoring Instrument (TROPOMI) over Tibetan Plateau lakes and attributed them to megacity-scale emissions from these lakes. Here we report serious anomalies in the NO2 retrievals over most of these lakes, possibly due to absorption in the water, which may have biased the NO2 retrieval results. Without addressing this potential absorption, it is premature to attribute any anomalies in tropospheric NO2 to emissions from Tibetan lakes, let alone estimate their magnitude.


Current potential of CH4 emission estimates using TROPOMI in the Middle East

September 2024

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103 Reads

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1 Citation

An improved divergence method has been developed to estimate annual methane (CH4) emissions from TROPOspheric Monitoring Instrument (TROPOMI) observations. It has been applied to the period of 2018 to 2021 over the Middle East, where the orography is complicated, and the mean mixing ratio of methane (XCH4) might be affected by albedos or aerosols over some locations. To adapt to extreme changes of terrain over mountains or coasts, winds are used with their divergent part removed. A temporal filter is introduced to identify highly variable emissions and to further exclude fake sources caused by retrieval artifacts. We compare our results to widely used bottom-up anthropogenic emission inventories: Emissions Database for Global Atmospheric Research (EDGAR), Community Emissions Data System (CEDS), and Global Fuel Exploitation Inventory (GFEI) over several regions representing various types of sources. The NOx emissions are from EDGAR and Daily Emissions Constrained by Satellite Observations (DECSO), and the industrial heat sources identified by Visible Infrared Imaging Radiometer Suite (VIIRS) are further used to better understand our resulting methane emissions. Our results indicate possibly large underestimations of methane emissions in metropolises like Tehran (up to 50 %) and Isfahan (up to 70 %) in Iran. The derived annual methane emissions from oil/gas production near the Caspian Sea in Turkmenistan are comparable to GFEI but more than 2 times higher than EDGAR and CEDS in 2019. Large discrepancies in the distribution of methane sources in Riyadh and its surrounding areas are found between EDGAR, CEDS, GFEI, and our emissions. The methane emission from oil/gas production to the east of Riyadh seems to be largely overestimated by EDGAR and CEDS, while our estimates as well as GFEI and DECSO NOx indicate much lower emissions from industrial activities. On the other hand, regions like Iran, Iraq, and Oman are dominated by sources from oil and gas exploitation that probably include more irregular releases of methane, with the result that our estimates, which include only invariable sources, are lower than the bottom-up emission inventories.


Citations (68)


... This discovery was based on emission inversion from the POMINO-TROPOMI tropospheric NO 2 vertical column density (VCD) satellite product 2 , which was derived on top of the satellite slant column density (SCD) data from KNMI 3 . Labzovskii et al. 4 proposed that the high NO 2 VCDs over the TP lakes could be alternatively explained as spectral contributions by absorption in lake water (chlorophyll) that were not accounted for in SCD fitting. This hypothesis lacks supporting evidence. ...

Reference:

Reply to: NO2 satellite retrievals biased by absorption in water
NO2 satellite retrievals biased by absorption in water

... CAMS produces NEE by calculating GEE and Re in the CHTESSEL module, which is the counterpart of CarbonTracker's CASA model. Soil respiration is parameterized within the Re calculation formula (Boussetta et al. 2013), and fire flux is provided from the CAMS Global Fire Assimilation System (GFAS) (Kaiser et al. 2012;Agustí-Panareda et al. 2023). NEE calculation in WRF-Chem is similar to that in CAMS, except that the VPRM module is used. ...

Technical note: The CAMS greenhouse gas reanalysis from 2003 to 2020

... La estimación del UVI se fundamenta en los procesos de absorción y dispersión de la radiación ultravioleta, principalmente debidos a la presencia de ozono y aerosoles en la atmósfera. Adicionalmente, el modelo simula la conversión de aerosoles y gases traza, así como la radiación absorbida y reflejada por la superficie y la atmósfera (Eskes et al., 2024). Para generar los datos de pronóstico de UVI primero se obtiene la irradiancia solar espectral en la superficie en el rango de 280 a 400 nm con una resolución de 5 nm, teniendo en cuenta el albedo de la superficie local, los aerosoles, las nubes y el ozono en el perfil del modelo. ...

Technical note: Evaluation of the Copernicus Atmosphere Monitoring Service Cy48R1 upgrade of June 2023

... Fioletov et al. [7] analysed the seasonal NO₂ distributions in urban, industrial, and rural areas at the global level using TROPOMI satellite data and enabled the identification of emission sources with these data. Liu et al. [8] improved the accuracy of atmospheric measurements and created highresolution emission maps using an improved TROPOMI tropospheric NO₂ product over Europe. ...

Global seasonal urban, industrial, and background NO 2 estimated from TROPOMI satellite observations

... The final results are further compared to the total anthropogenic CH 4 emissions from Emissions Database for Global Atmospheric Research (EDGAR) v7.0 (Crippa et al., 2022) and Community Emissions Data System (CEDS) v_2021_04_21 (O'Rourke et al., 2021). Other auxiliary datasets, such as the methane emissions from fuel exploitation predicted by GFEI v2 (Scarpelli et al., 2022) and total anthropogenic NO x emissions from EDGAR v6.1 and Daily Emissions Constrained by Satellite Observations (DECSO) v6.2 (van der A et al., 2024;Ding et al., 2020;Mijling and van der A, 2012), are used for a better interpretation of our results. ...

Monitoring European anthropogenic NOx emissions from space

... In contrast, satellite observations, available in real time, provide comprehensive and independent information about the global distribution of the total amount of NO 2 in the atmosphere with city-scale resolution, allowing the quantification of major point sources (Beirle et al., 2021(Beirle et al., , 2023Chen et al., 2023;Dammers et al., 2024;Fioletov et al., 2022). These observations can be linked to emissions by accounting for the chemical conversion and transport of the atmospheric NO 2 . ...

Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?

... August 2019), and the high signal-to-noise ratio, make the product suitable for examining emissions from diverse sources such as city emissions (Lorente et al., 2019;Pommier, 2022;Xue et al., 2022;Zhang et al., 2023), power plants (Goldberg et al., 2019;Saw et al., 2021;Skoulidou et al., 2021;Krol et al., 2024), oil and gas production (Dix et al., 2022), individual ships 55 (Georgoulias et al., 2020;Kurchaba et al., 2022;Riess et al., 2024), lighting (Allen et al., 2021;Zhang et al., 2022), soil and croplands (Huber et al., 2020). Beyond the NO x emissions, the TROPOMI instrument has also been employed to derive emission datasets for CH 4 , SO 2 (Chen et al., 2024;Fioletov et al., 2020) and CO (Leguijt et al., 2023). ...

SO 2 emissions and lifetimes derived from TROPOMI observations over India using a flux-divergence method

... DECSO is able to provide total emissions for short-lived chemical species, including new emission sources that may be missing from bottom-up inventories. DECSO uses super-observations of the NO 2 column from the surface to 700 hPa, which removes most of the free tropospheric NO 2 (Rijsdijk et al., 2024;. Thus, DECSO total NO x emissions do not include the lightning NO x emissions (van der A et al., 2024). ...

Quantifying uncertainties of satellite NO 2 superobservations for data assimilation and model evaluation

... Space-borne remote sensing instruments have played a key role in monitoring atmospheric composition since the 1990s Bovensmann et al. 1999;Drummond and Mand 1996;Veefkind et al. 2006Veefkind et al. , 2012Zoogman et al. 2017; Levelt et al. 2018;Kim et al. 2020, among others). Satellite observations have been used with sophisticated models to help develop policies to reduce emissions (e.g., Duncan et al. 2016;Jiang et al. 2018), improve our knowledge about air pollution (e.g., Fu et al. 2007;Silvern et al. 2019;Yang et al. 2023b), and better forecast air quality (e.g., Peuch et al. 2022;Eskes et al. 2024). ...

Technical Note: Evaluation of the Copernicus Atmosphere Monitoring Service Cy48R1 upgrade of June 2023

... In order to associate the super-observations to an actual AK profile, the super-observations have been taken as the observation (TVCD and AKs) corresponding to the value closest to the mean of the OMI or TROPOMI TVCDs within the 0.5°×0.5°model grid-cell and 255 within the CHIMERE physical time step of about 5-10 minutes, as in Plauchu et al. (2024). The choice of the value closest to the mean is different from Fortems-Cheiney et al. (2021b), initially taking the median of the observations for defining superobservations. ...

NO x emissions in France in 2019–2021 as estimated by the high spatial resolution assimilation of TROPOMI NO 2 observations