Articles | Volume 13, issue 6
https://doi.org/10.5194/essd-13-2995-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-2995-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
24 Jun 2021
Data description paper |
| 24 Jun 2021
| 24 Jun 2021
Catalog of NOx emissions from point sources as derived from the divergence of the NO2 flux for TROPOMI
Satellitenfernerkundung, Max-Planck-Institut für Chemie (MPI-C), Mainz, Germany
Christian Borger
Satellitenfernerkundung, Max-Planck-Institut für Chemie (MPI-C), Mainz, Germany
Steffen Dörner
Satellitenfernerkundung, Max-Planck-Institut für Chemie (MPI-C), Mainz, Germany
Henk Eskes
Satellite Observations Department, Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Vinod Kumar
Satellitenfernerkundung, Max-Planck-Institut für Chemie (MPI-C), Mainz, Germany
Adrianus de Laat
Satellite Observations Department, Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Thomas Wagner
Satellitenfernerkundung, Max-Planck-Institut für Chemie (MPI-C), Mainz, Germany
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Cited
59 citations as recorded by crossref.
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- Quantifying urban, industrial, and background changes in NO2 during the COVID-19 lockdown period based on TROPOMI satellite observations V. Fioletov et al. 10.5194/acp-22-4201-2022
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- Two years of satellite-based carbon dioxide emission quantification at the world's largest coal-fired power plants D. Cusworth et al. 10.5194/acp-23-14577-2023
- Model-free daily inversion of NOx emissions using TROPOMI (MCMFE-NOx) and its uncertainty: Declining regulated emissions and growth of new sources K. Qin et al. 10.1016/j.rse.2023.113720
- Estimating surface NO2 concentrations over Europe using Sentinel-5P TROPOMI observations and Machine Learning S. Shetty et al. 10.1016/j.rse.2024.114321
- Reconciliation of asynchronous satellite-based NO2 and XCO2 enhancements with mesoscale modeling over two urban landscapes R. Lei et al. 10.1016/j.rse.2022.113241
- UNCERTAINTY QUANTIFICATION BY GAUSSIAN RANDOM FIELDS FOR POINT-LIKE EMISSIONS FROM SATELLITE OBSERVATIONS T. Härkönen et al. 10.1615/Int.J.UncertaintyQuantification.2023044906
- Nitrogen dioxide spatiotemporal variations in the complex urban environment of Athens, Greece T. Drosoglou et al. 10.1016/j.atmosenv.2023.120115
- Global seasonal urban, industrial, and background NO2 estimated from TROPOMI satellite observations V. Fioletov et al. 10.5194/acp-25-575-2025
- SO2 emissions derived from TROPOMI observations over India using a flux-divergence method with variable lifetimes Y. Chen et al. 10.5194/acp-25-1851-2025
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- Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa J. Hakkarainen et al. 10.1016/j.apr.2024.102171
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- Air quality impacts of COVID-19 lockdown measures detected from space using high spatial resolution observations of multiple trace gases from Sentinel-5P/TROPOMI P. Levelt et al. 10.5194/acp-22-10319-2022
- Maritime sector contributions on NO2 surface concentrations in major ports of the Mediterranean Basin A. Pseftogkas et al. 10.1016/j.apr.2024.102228
- Identification of NO emissions and source characteristics by TROPOMI observations – A case study in north-central Henan, China H. Sheng et al. 10.1016/j.scitotenv.2024.172779
- Building a bridge: characterizing major anthropogenic point sources in the South African Highveld region using OCO-3 carbon dioxide snapshot area maps and Sentinel-5P/TROPOMI nitrogen dioxide columns J. Hakkarainen et al. 10.1088/1748-9326/acb837
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- Identifying and accounting for the Coriolis effect in satellite NO2 observations and emission estimates D. Potts et al. 10.5194/acp-23-4577-2023
- Quantifying NOx Emissions from U.S. Oil and Gas Production Regions Using TROPOMI NO2 B. Dix et al. 10.1021/acsearthspacechem.1c00387
- Evaluating Machine Learning and Remote Sensing in Monitoring NO2 Emission of Power Plants A. Alnaim et al. 10.3390/rs14030729
- The attempt to estimate annual variability of NOx emission in Poland using Sentinel-5P/TROPOMI data J. Godłowska et al. 10.1016/j.atmosenv.2022.119482
- Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine I. Ialongo et al. 10.1038/s41598-023-42118-w
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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 F. Cifuentes et al. 10.5194/gmd-18-621-2025
- Derivation of Emissions From Satellite‐Observed Column Amounts and Its Application to TROPOMI NO2 and CO Observations K. Sun 10.1029/2022GL101102
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- Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset J. Hakkarainen et al. 10.3389/frsen.2022.878731
- Quantifying NOxpoint sources with Landsat and Sentinel-2 satellite observations of NO2plumes D. Varon et al. 10.1073/pnas.2317077121
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- An improved understanding of NOx emissions in South Asian megacities using TROPOMI NO2 retrievals B. de Foy & J. Schauer 10.1088/1748-9326/ac48b4
- Identifying missing sources and reducing NOx emissions uncertainty over China using daily satellite data and a mass-conserving method L. Lu et al. 10.5194/acp-25-2291-2025
- Deep transfer learning method for seasonal TROPOMI XCH4 albedo correction A. Bradley et al. 10.5194/amt-18-1675-2025
- Nitrogen oxides emissions from selected cities in North America, Europe, and East Asia observed by the TROPOspheric Monitoring Instrument (TROPOMI) before and after the COVID-19 pandemic C. Lonsdale & K. Sun 10.5194/acp-23-8727-2023
- Variability of nitrogen oxide emission fluxes and lifetimes estimated from Sentinel-5P TROPOMI observations K. Lange et al. 10.5194/acp-22-2745-2022
- Estimations of NOxemissions, NO2lifetime and their temporal variation over three British urbanised regions in 2019 using TROPOMI NO2observations M. Pommier 10.1039/D2EA00086E
- Considerable Unaccounted Local Sources of NOx Emissions in China Revealed from Satellite H. Kong et al. 10.1021/acs.est.1c07723
- Spatio-Temporal Analysis of NO2 and CO Production with Sentinel 5P Tropomy Time Series Images: The Case of Torbalı and Kemalpaşa Districts of Izmir Province in Türkiye . Münevver Gizem Gümüş 10.32628/CSEIT2511117
58 citations as recorded by crossref.
- Stereoscopic hyperspectral remote sensing of the atmospheric environment: Innovation and prospects C. Liu et al. 10.1016/j.earscirev.2022.103958
- Monitoring European anthropogenic NOx emissions from space R. van der A et al. 10.5194/acp-24-7523-2024
- Quantifying urban, industrial, and background changes in NO2 during the COVID-19 lockdown period based on TROPOMI satellite observations V. Fioletov et al. 10.5194/acp-22-4201-2022
- Impact of Hurricane Ida on Nitrogen Oxide Emissions in Southwestern Louisiana Detected from Space T. Lee et al. 10.1021/acs.estlett.2c00414
- A lightweight NO2-to-NOx conversion model for quantifying NOx emissions of point sources from NO2 satellite observations S. Meier et al. 10.5194/acp-24-7667-2024
- Two years of satellite-based carbon dioxide emission quantification at the world's largest coal-fired power plants D. Cusworth et al. 10.5194/acp-23-14577-2023
- Model-free daily inversion of NOx emissions using TROPOMI (MCMFE-NOx) and its uncertainty: Declining regulated emissions and growth of new sources K. Qin et al. 10.1016/j.rse.2023.113720
- Estimating surface NO2 concentrations over Europe using Sentinel-5P TROPOMI observations and Machine Learning S. Shetty et al. 10.1016/j.rse.2024.114321
- Reconciliation of asynchronous satellite-based NO2 and XCO2 enhancements with mesoscale modeling over two urban landscapes R. Lei et al. 10.1016/j.rse.2022.113241
- UNCERTAINTY QUANTIFICATION BY GAUSSIAN RANDOM FIELDS FOR POINT-LIKE EMISSIONS FROM SATELLITE OBSERVATIONS T. Härkönen et al. 10.1615/Int.J.UncertaintyQuantification.2023044906
- Nitrogen dioxide spatiotemporal variations in the complex urban environment of Athens, Greece T. Drosoglou et al. 10.1016/j.atmosenv.2023.120115
- Global seasonal urban, industrial, and background NO2 estimated from TROPOMI satellite observations V. Fioletov et al. 10.5194/acp-25-575-2025
- SO2 emissions derived from TROPOMI observations over India using a flux-divergence method with variable lifetimes Y. Chen et al. 10.5194/acp-25-1851-2025
- Quantifying NOx emissions in Egypt using TROPOMI observations A. Rey-Pommier et al. 10.5194/acp-22-11505-2022
- High-resolution mapping of nitrogen oxide emissions in large US cities from TROPOMI retrievals of tropospheric nitrogen dioxide columns F. Liu et al. 10.5194/acp-24-3717-2024
- Observationally constrained global NOx and CO emissions variability reveals sources which contribute significantly to CO2 emissions S. Wang et al. 10.1038/s41612-025-00977-2
- S‐5P/TROPOMI‐Derived NOxEmissions From Copper/Cobalt Mining and Other Industrial Activities in the Copperbelt (Democratic Republic of Congo and Zambia) S. Martínez‐Alonso et al. 10.1029/2023GL104109
- Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa J. Hakkarainen et al. 10.1016/j.apr.2024.102171
- Evaluating NOx stack plume emissions using a high-resolution atmospheric chemistry model and satellite-derived NO2 columns M. Krol et al. 10.5194/acp-24-8243-2024
- Evaluation of the nitrogen oxide emission inventory with TROPOMI observations Y. Chen et al. 10.1016/j.atmosenv.2023.119639
- High-resolution observations of NO2 and CO2 emission plumes from EnMAP satellite measurements C. Borger et al. 10.1088/1748-9326/adc0b1
- A simplified non-linear chemistry transport model for analyzing NO2 column observations: STILT–NOx D. Wu et al. 10.5194/gmd-16-6161-2023
- Air quality impacts of COVID-19 lockdown measures detected from space using high spatial resolution observations of multiple trace gases from Sentinel-5P/TROPOMI P. Levelt et al. 10.5194/acp-22-10319-2022
- Maritime sector contributions on NO2 surface concentrations in major ports of the Mediterranean Basin A. Pseftogkas et al. 10.1016/j.apr.2024.102228
- Identification of NO emissions and source characteristics by TROPOMI observations – A case study in north-central Henan, China H. Sheng et al. 10.1016/j.scitotenv.2024.172779
- Building a bridge: characterizing major anthropogenic point sources in the South African Highveld region using OCO-3 carbon dioxide snapshot area maps and Sentinel-5P/TROPOMI nitrogen dioxide columns J. Hakkarainen et al. 10.1088/1748-9326/acb837
- Quantifying Urban Daily Nitrogen Oxide Emissions from Satellite Observations T. Tang et al. 10.3390/atmos15040508
- Benchmarking data-driven inversion methods for the estimation of local CO2 emissions from synthetic satellite images of XCO2 and NO2 D. Santaren et al. 10.5194/amt-18-211-2025
- Satellite detected weak decline of nitrogen oxides emissions in economically small cities of China H. Kong et al. 10.1088/1748-9326/ade170
- Monitoring and quantifying CO2emissions of isolated power plants from space X. Lin et al. 10.5194/acp-23-6599-2023
- Identifying and accounting for the Coriolis effect in satellite NO2 observations and emission estimates D. Potts et al. 10.5194/acp-23-4577-2023
- Quantifying NOx Emissions from U.S. Oil and Gas Production Regions Using TROPOMI NO2 B. Dix et al. 10.1021/acsearthspacechem.1c00387
- Evaluating Machine Learning and Remote Sensing in Monitoring NO2 Emission of Power Plants A. Alnaim et al. 10.3390/rs14030729
- The attempt to estimate annual variability of NOx emission in Poland using Sentinel-5P/TROPOMI data J. Godłowska et al. 10.1016/j.atmosenv.2022.119482
- Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine I. Ialongo et al. 10.1038/s41598-023-42118-w
- Diurnal NO emission underestimation constrained using overlapping TROPOMI swaths Q. He et al. 10.1016/j.atmosenv.2025.121354
- Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes F. Cifuentes et al. 10.5194/gmd-18-621-2025
- Derivation of Emissions From Satellite‐Observed Column Amounts and Its Application to TROPOMI NO2 and CO Observations K. Sun 10.1029/2022GL101102
- Estimating global 0.1° scale gridded anthropogenic CO2 emissions using TROPOMI NO2 and a data-driven method Y. Zhang et al. 10.1016/j.scitotenv.2024.175177
- Potential of TROPOMI for understanding spatio-temporal variations in surface NO2 and their dependencies upon land use over the Iberian Peninsula H. Petetin et al. 10.5194/acp-23-3905-2023
- Version 2 of the global catalogue of large anthropogenic and volcanic SO2 sources and emissions derived from satellite measurements V. Fioletov et al. 10.5194/essd-15-75-2023
- Improved catalog of NOx point source emissions (version 2) S. Beirle et al. 10.5194/essd-15-3051-2023
- Unveiling nitrogen oxide emissions from open-pit copper mines through satellite observations I. Ialongo et al. 10.1088/1748-9326/adb767
- Widespread missing super-emitters of nitrogen oxides across China inferred from year-round satellite observations Y. Pan et al. 10.1016/j.scitotenv.2022.161157
- Evaluating NOx emissions and their effect on O3 production in Texas using TROPOMI NO2 and HCHO D. Goldberg et al. 10.5194/acp-22-10875-2022
- Estimating surface-level nitrogen dioxide concentrations from Sentinel-5P/TROPOMI observations in Finland H. Virta et al. 10.1016/j.atmosenv.2023.119989
- 大气CO2成像卫星遥感的点源排放分辨能力影响因素分析 李. Li Chao et al. 10.3788/AOS231336
- Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset J. Hakkarainen et al. 10.3389/frsen.2022.878731
- Quantifying NOxpoint sources with Landsat and Sentinel-2 satellite observations of NO2plumes D. Varon et al. 10.1073/pnas.2317077121
- U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers J. Bruno et al. 10.5194/amt-17-2625-2024
- 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)? E. Dammers et al. 10.5194/gmd-17-4983-2024
- An improved understanding of NOx emissions in South Asian megacities using TROPOMI NO2 retrievals B. de Foy & J. Schauer 10.1088/1748-9326/ac48b4
- Identifying missing sources and reducing NOx emissions uncertainty over China using daily satellite data and a mass-conserving method L. Lu et al. 10.5194/acp-25-2291-2025
- Deep transfer learning method for seasonal TROPOMI XCH4 albedo correction A. Bradley et al. 10.5194/amt-18-1675-2025
- Nitrogen oxides emissions from selected cities in North America, Europe, and East Asia observed by the TROPOspheric Monitoring Instrument (TROPOMI) before and after the COVID-19 pandemic C. Lonsdale & K. Sun 10.5194/acp-23-8727-2023
- Variability of nitrogen oxide emission fluxes and lifetimes estimated from Sentinel-5P TROPOMI observations K. Lange et al. 10.5194/acp-22-2745-2022
- Estimations of NOxemissions, NO2lifetime and their temporal variation over three British urbanised regions in 2019 using TROPOMI NO2observations M. Pommier 10.1039/D2EA00086E
- Considerable Unaccounted Local Sources of NOx Emissions in China Revealed from Satellite H. Kong et al. 10.1021/acs.est.1c07723
Latest update: 09 Jul 2025
Short summary
A catalog of point sources of nitrogen oxides was created using satellite observations of NO2. Key for the identification of point sources was the divergence, i.e., the difference between upwind and downwind levels of NO2.
The catalog lists 451 locations, of which 242 could be automatically matched to power plants. Other point sources are metal smelters, cement plants, or industrial areas. The catalog thus allows checking and improving of existing emission inventories.
A catalog of point sources of nitrogen oxides was created using satellite observations of NO2....
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