Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods


  • NO2 to NOx scaling factors calculated from the MicroHH large-eddy simulations.
  • Optimal scaling factors depend on the emission inversion method.
  • Scaling factors applied to derive NOx emissions from S5P/TROPOMI NO2 observations.
  • Optimal scaling factors are substantially higher than the values previously used.

We have a new paper in Atmospheric Pollution Research!

In this paper, we propose improved nitrogen dioxide (NO2) to nitrogen oxide (NOx) scaling factors for several data-driven methods that are used for the estimation of NOx power plant emissions from satellite observations of NO2. The scaling factors are deduced from high-resolution simulations of power plant plumes with the MicroHH large-eddy simulation model with a simplified chemistry and then applied to Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) NO2 satellite observations over the Matimba/Medupi power stations in South Africa.

In this new paper, we show that due to the non-linear chemistry the optimal NO2 to NOx scaling factors depend on both the method employed and the specific segments of the plume from which emission estimate is derived. The scaling factors derived from the MicroHH simulations in this study are substantially (more than 50%) higher than the typical values used in the literature with actual NO2 observations. The results highlight the challenge in appropriately accounting for the conversion from NO2 to NOx when estimating point source emissions from satellite NO2 observations.


Janne Hakkarainen, Gerrit Kuhlmann, Erik Koene, Diego Santaren, Sandro Meier, Maarten C. Krol, Bart J.H. van Stratum, Iolanda Ialongo, Frédéric Chevallier, Johanna Tamminen, Dominik Brunner, Grégoire Broquet,: 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, Atmospheric Pollution Research, Volume 15, Issue 7,, 2024.

Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine

Satellite observations show significantly reduced air pollution levels over the major Ukrainian cities, power plants and industrial areas.

Since February 2022, the full-scale war in Ukraine has been strongly affecting society and economy in Ukraine. Satellite observations provide crucial information to objectively monitor and assess the impacts of the war. A new paper published today on Scientific Reports utilizes satellite observations of air pollutants and other relevant parameters from multiple platforms to assess the impacts of the ongoing war on the Ukrainian society. Satellite observations show that the concentrations of nitrogen dioxide (NO₂), which is emitted through fossil fuel combustion processes, declined in 2022 over the major Ukrainian cities, power plants and industrial areas by 15–46%.

Such reductions reflect the decrease in population and corresponding emissions from the transport and commercial or residential sectors as well as the decline in industrial production, especially from the metallurgic and chemical industry, which led to a reduction in power demand and corresponding electricity production from power plants. Carbon dioxide (CO₂) observations also indicate reductions in fossil fuel combustion, especially in eastern Ukraine, where the largest emission sources are located.

Difference of the March-August mean tropospheric NO2 columns between 2022 and 2021 based on S5P/TROPOMI observations. Blue colors indicate reductions observed in 2022. Black dots correspond to the major cities, industrial areas and power plants.

“During peaceful times, reductions in nitrogen dioxide concentrations as those observed here would be considered as a welcome improvement of air quality and human health. In this case, the observed changes tell a different story about the extent of the disruption caused by the war on the Ukrainian society and economy. Also, the reductions in fossil fuel consumption in Ukraine might have been partly offset by an increase elsewhere”, explains senior researcher at the Finnish Meteorological Institute Iolanda Ialongo, who led the work.

Exceptional fire patterns near the front line
Satellite imagery and fire detections indicate an anomalous distribution of fires along the front line, which are attributable to shelling or other war-related fires, rather than the typical homogeneously distributed fires related to crop harvesting. Satellite imagery data also show drastic changes over the city of Mariupol, which was attacked during the first three months of the war.

The signal from the hot smokes from the metallurgic industrial facilities in the city disappears from the satellite imagery after March 2022, which suggest an interruption of industrial activities, and, correspondingly, NO₂ levels decreased.

The results are based on the NO₂ retrievals from the European TROPOMI (TROPOspheric Monitoring Instrument), onboard the Sentinel 5 Precursor satellite, and the CO₂ observations from the NASA’s OCO-2 satellite. Also satellite imagery from the Sentinel 2 satellite was analyzed as well as fire detectionsfrom the Visible Infrared Imaging Radiometer Suite (VIIRS).

The research was carried on at the Finnish Meteorological Institute together with colleagues from the University of Lviv (Ukraine) and USRA (USA). The Finnish part of the research was supported by the Ministry for Foreign Affairs of Finland via theInterinstitutional Development Cooperation Instrument (ICI), UHMC-FMI Meteorology project and the Research Council of Finland.

Reference: Ialongo, I., Bun, R., Hakkarainen, J. et al. Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine. Sci Rep13, 14954 (2023).

Building a Bridge: Estimating Carbon Dioxide Emissions Using Satellites

A team of researchers estimated the carbon dioxide (CO2) emissions from coal-fired power plants and other major anthropogenic point sources in the South African Highveld region using space-based data. The results indicate that the CO2 emissions can be obtained also in challenging cases where the plumes from multiple sources overlap.

The article analyses the emissions of six power stations (Kendal, Kriel, Matla, Majuba, Tutuka and Grootvlei) and the largest single emitter of greenhouse gas in the world, Secunda CTL synthetic fuel plant. The annual CO₂ emissions of the Secunda CTL exceed the emissions of several European countries, including Finland, Norway, and Portugal. 

Overall, the space-based emission estimates are in good agreement with the emission inventories. Thus, satellite observations can be used for CO2 emission estimation and are particularly useful when no other information is available.

Orbiting Carbon Observatory-3 mission operates on the International Space Station (ISS). To support the quantification and monitoring of anthropogenic CO₂ emissions, OCO-3 incorporates a new key capability that provides observations in Snapshot Area Maps (SAMs), providing contiguous images over regions as large as 80 km by 80 km in two minutes. Altogether the article analyzes six OCO-3 SAMs jointly with Sentinel-5P/TROPOMI nitrogen dioxide (NO2) columns.

Sentinel-5P/TROPOMI NO₂ and OCO-3 XCO₂ SAM observations on 21 January 2022.

The new article is a continuation of the previous work where the authors studied the emissions and NOx-to-CO₂ emission ratio of the isolated Matimba power station. The article extends the method to challenging cases where CO₂ plumes from multiple sources overlap.

The applicability of similar emission estimation approaches for future satellite missions such as the Copernicus Carbon Dioxide Monitoring mission CO2M are discussed. CO2M is Copernicus Sentinel Expansion missions and will focus on carbon dioxide released into the atmosphere specifically through human activity.

The research was carried on at Finnish Meteorological Institute together with colleagues from USRA, Colorado State University and Caltech/JPL. The Finnish part of the research was supported by European Space Agency (DACES), Academy of Finland (CitySpot, CoE inverse and ACCC) and EU-H2020 CoCO2.

The full publication by Hakkarainen and co-authors can be found at the following link:

TanSat Successfully Detects Human-Caused CO2 for the First Time

Launched in 2016, TanSat is China’s first global carbon dioxide monitoring satellite. Tan is the Chinese pronunciation of carbon. While TanSat has been providing researchers with data for several years, new algorithms were recently added to the TanSat instruments that greatly improved TanSat’s measurement precision.

The research team conducted their study by looking at two sets of measurements collected over two cities. The scientists used TanSat carbon dioxide data captured in May 2018 near Tangshan, China, and in March 2018 near Tokyo, Japan. They compared the TanSat data to nitrogen dioxide measurements captured by the TROPOspheric Monitoring Instrument onboard the Copernicus Sentinel-5 Precursor satellite on the same dates over the same cities.

“We analyzed TanSat data in synergy with European Copernicus Sentinel-5 Precursor TROPOMI nitrogen dioxide observations to help the detection of anthropogenic plumes and to analyze the carbon dioxide-to-nitrogen dioxide ratio,” said Dongxu Yang, from the Institute of Atmospheric Physics, Chinese Academy of Sciences.

The left panel illustrates TROPOMI NO2 observations overlapped by TanSat XCO2 observation near Tangshan (China) on 6 May 2018. ERA5 wind fields are shown as arrows. The XCO2 background is calculated as a median, north of the white dashed line. The right panels (top and bottom) show the XCO2 and NO2 observations (respectively) along the TanSat track. The black dots indicate the running mean. Orange colors indicate the XCO2 converted from NO2 tropospheric columns via a linear fit.

Their two case studies show TanSat carbon dioxide measurements have the capability to capture the anthropogenic variations in the plume and have spatial patterns like that of the TROPOspheric Monitoring Instrument’s nitrogen dioxide observations. In addition, the carbon dioxide-to-nitrogen dioxide ratio in Tangshan, China, and Tokyo, Japan, align with the emission inventories.

“This is an important step in TanSat data analysis. The next step is to infer emissions and to prepare for the TanSat-2 constellation including the joint analysis of CO2 and NO2 plumes,” said Janne Hakkarainen, from the Finnish Meteorological Institute.

Looking ahead, the team has plans to expand this research. “The TanSat is our first attempt on global carbon monitoring. The next generation of China’s Global Carbon Dioxide Monitoring Satellite mission, TanSat-2, is now in the design phase,” said Yi Liu, from the Institute of Atmospheric Physics, Chinese Academy of Sciences.

According to Liu, TanSat-2’s target measurements will focus on cities with an 800-1000 kilometer (500-620 mile) wide swath to record the gradient of carbon dioxide from city central to rural areas using an imaging process and a 500-meter (1600-foot) footprint size to improve the emission estimation accuracy. TanSat-2 will be a constellation of satellites distributed into at least two orbits in the morning and afternoon to cover a city or a point source twice a day.

“Our goal is to use satellite measurements to improve our knowledge of the carbon cycle and to further analyze and constraint the carbon dioxide sources and sinks and their uncertainties,” said Liu.

Reference: “Detection of Anthropogenic CO2 Emission Signatures with TanSat CO2 and with Copernicus Sentinel-5 Precursor (S5P) NO2 Measurements: First Results” by Dongxu Yang, Janne Hakkarainen, Yi Liu, Iolanda Ialongo, Zhaonan Cai and Johanna Tamminen, 25 October 2022, Advances in Atmospheric Sciences.

Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method

Since the Paris Agreement was adopted in 2015, the role of space-based observations for monitoring anthropogenic greenhouse gas (GHG) emissions has increased. To meet the requirements for monitoring carbon dioxide (CO2) emissions, the European Copernicus programme is preparing a dedicated CO2 Monitoring (CO2M) satellite constellation that will provide CO2 and nitrogen dioxide (NO2) observations at 4 km2 resolution along a 250 km wide swath.

Simulated CO2M observations. Figure by Gerrit Kuhlmann, Empa.

In a new paper, we adapt the recently developed divergence method to derive both CO2 and nitrogen oxide (NOx) emissions of cities and power plants from a CO2M satellite constellation by using synthetic observations from the COSMO-GHG model. Due to its long lifetime, the large CO2 atmospheric background needs to be removed to highlight the anthropogenic enhancements before calculating the divergence. Since the CO2 noise levels are large compared to the anthropogenic enhancements, we apply different denoising methods and compare the effect on the CO2 emission estimates. The annual NOx and CO2 emissions estimated from the divergence maps using the peak fitting approach are in agreement with the expected values, although with larger uncertainties for CO2. We also consider the possibility to use co-emitted NOx emission estimates for quantifying the CO2emissions, by using source-specific NOx-to-CO2 emission ratios derived directly from satellite observations. In general, we find that the divergence method provides a promising tool for estimating CO2 emissions, alternative to typical methods based on inverse modeling or on the analysis of individual CO2 plumes.

Reference: Janne Hakkarainen, Iolanda Ialongo, Erik Koene, Monika E. Szeląg, Johanna Tamminen, Gerrit Kuhlmann, Dominik Brunner: Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset, Frontiers in Remote Sensingvol 3, 2022, doi:10.3389/frsen.2022.878731, Link

Carbon dioxide emission plumes from a large power station detected from space

Researchers at the Finnish Meteorological Institute developed a new methodology to derive source-specific NOₓ-to-CO₂ emission ratios using satellite observations. The method was applied to Matimba power station in South Africa. The results can be used to estimate carbon dioxide emissions.

Since the Paris agreement was adopted in 2015, the role of satellite observations in understanding anthropogenic CO2 emissions has become increasingly important. Currently, the NASA’s CO2 instrument Orbiting Carbon Observatory-2 (OCO-2), launched in 2014, provides CO2 observations with the best coverage and resolution. However, the observations are obtained on a narrow swath (less than 10 km), which does allow the detection of the cross-sections of the emission plumes, but not the plumes in their entirety. Satellite observations of co-emitted species, such as NO2, facilitate the detection of the CO2 emission plumes. The European Commission is currently planning a new CO2 monitoring mission CO2M via the Copernicus Programme, which will observe both CO2 and NO2 over a larger swath (over 250 km).

Estimating CO2 emissions from individual sources using satellite data can be challenging due to the large background levels, while it is easier for short-lived gases like NO2. In a recently published study, a new methodology to calculate source-specific NOₓ-to-CO₂ emission ratio from satellite observations is developed. This ratio provides information on how clean the employed technology is and can be used to convert NOₓ emission into CO2 emission. The method was tested for the Matimba power station in South Africa, which is an optimal case study as it is a large emission source with several satellite overpasses, and it is also well isolated from other sources.

OCO-2 and TROPOMI observations near Matimba power station (red triangle) in South Africa between May 2018 and November 2020. Image: Hakkarainen et al. 2021. CC BY 4.0.

The results are based on the CO2 observations from the NASA’s OCO-2 satellite and the NO2 retrievals from the European TROPOMI (TROPOspheric Monitoring Instrument), operating onboard the Sentinel 5 Precursor satellite since late 2017. During the 2018–2020 period, 14 collocations over Matimba enabled the simultaneous detection of the CO2 and NO2 plumes. The mean NOx-to-CO2 emission ratio was estimated as (2.6 ± 0.6) × 10⁻³ and the CO2 emission as 60 kton/day. The obtained CO₂ emission estimates are similar to those reported in existing inventories such as ODIAC.

The research was carried on in the DACES project, which focuses on detecting anthropogenic CO₂ emissions sources by exploiting the synergy between satellite-based observations of short-lived polluting gases (such as NO₂) and greenhouse gases.

The full publication by Hakkarainen and co-authors can be found at the following link:

Virtual Inverse Days 2020

Virtual Inverse Days 2020

University of Helsinki and Finnish Meteorological Institute co-organized 26th Inverse Days of the Finnish Inverse Problems Society. This year the conference was organized virtually, and the chair of the Scientific committee was Tatiana Bubba from the University of Helsinki. The conference had altogether 59 scientific talks and more than 180 registered participants.

Inverse Days is the annual scientific conference of the Finnish Inverse Problems Society (FIPS). The first Inverse Days were organized at the University of Oulu in 1995. This year the conference was organized virtually for the first time due to the global COVID-19 pandemic. The conference was divided in 10 scientific session. The sessions covered both theoretical and applied inverse problems. Application areas included 3D X-ray tomography, electrical impedance tomography, forestry, uncertainty quantification and atmospheric inverse problems among others. The themes followed the themes of the Finnish Centre of Excellence in Inverse Modelling and Imaging. The session number 2 was dedicated to the memory of the late Mikko Kaasalainen (born 1965, died 12 April 2020), who was a professor of mathematics at the Tampere University and an important member of the Finnish Inverse Problems Society. The conference had 25 highlight talks, 29 regular talks and five plenary talks. The plenary talks were given by Chris Johnson (U. Utah), Silvia Gazzola (U. Bath), Valery Serov (U. Oulu), Simon Pfreunschuh (Chalmers U. Tech.) and Barbara Kaltenbacher (U. Klagenfurt). Number of registered participants was all-time record: 185.

In addition to scientific program, the conference also had a special session to celebrate the 60th birthday of Prof. Erkki Somersalo, the founding president of FIPS. The birthday program included scientific talks related to Erkki Somersalo’s research and career along with more humoristic ones. Master of the ceremony was Prof. Samuli Siltanen, the current president of FIPS. For the first time, the Inverse days also had virtual lab excursions. The lab excursion included: 

  • X-ray Tomography Laboratory (UH), Alexander Meaney
  • Spectrometers in Atmospheric Measurements (FMI), Tomi Karppinen
  • Log X-ray Systems (Finnos Oy), Jere Heikkinen
  • Biomed. Optical Imaging and Ultrasound Lab (UEF), Aki Pulkkinen
  • Process Tomography Laboratory (UEF), Aku Seppänen

Virtual lab excursions will be also uploaded to the Inverse Problems YouTube channel:

Please pay extra attention to the amazing short film by Aku Seppänen!

The Inverse Days week also included a special session “Women in FIPS”, and the annual meeting of the Finnish Inverse Problems Society.

The Finnish Inverse Prize, annual award of the Finnish Inverse Problems Society, was awarded to Jesse Railo who defended his PhD thesis “Geodesic Tomography Problems on Riemannian Manifold” with distinction at the University of Jyväskylä in 2019. In addition to University of Jyväskylä, Jesse has also worked at U. Tampere, U. Helsinki and the Finnish Meteorological Institute, and is now a Postdoctoral scientist at the ETH Zürich. Congratulations Jesse!

The scientific committee of the conference was

  • Tatiana Bubba (chair)
  • Janne Hakkarainen
  • Marko Laine
  • Matti Lassas
  • Samuli Siltanen
  • Johanna Tamminen

Special thanks to Antti Mikkonen for his work on putting together the Virtual Lab tours, Rashmi Murthy for taking care excellently of the technical arrangements for the conference and Lauri Ylinen for his work on the website. A job well done!

“I love math” logo: Joe Volzer

Conference website:

Anthropogenic CO2 emission sources detected from space

Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas and its increase in the atmosphere is responsible for the global warming. CO2 is emitted into the atmosphere by the burning of fossil fuels. Satellite-based observations provide information on the concentration of carbon dioxide (i.e., column-averaged CO2 dry air mole fraction, XCO2) around the globe.

Because of its long lifetime, carbon dioxide increases in the atmosphere and gets transported by the winds very far from the emission sources.

A recent study introduced the concept of XCO2 anomaly (i.e. the difference from the daily background over a certain area), which provides maps of the distribution of the CO2 emission areas worldwide.

Janne Hakkarainen, from the Finnish Meteorological Institute (FMI), comments: “The map shows positive XCO2anomaly over the major industrial areas: China, eastern USA, central Europe, India, and the Highveld region in South Africa. Also, we find positive anomalies over biomass burning areas (for example in Africa and Indochina) during different fire seasons. On the other hand, the largest negative anomalies correspond to the growing season in the middle latitudes”. The anomaly maps are based on the observations collected by the NASA’s OCO-2 (Orbiting Carbon Observatory-2) mission, which began operating in September 2014.

Comparing the XCO2 anomaly maps to short-lived polluting gases, such as nitrogen dioxide (NO2) observations derived from the Copernicus Sentinel-5P’s TROPOMI (TROPOspheric Monitoring Instrument), provides further insights on the spatial patterns of the carbon dioxide emission sources.

Using NO2 concentrations as indicator of anthropogenic fossil fuel combustion, helps in identifying anthropogenic XCO2 enhancement as visible, for example, over the Highveld region in South Africa,” continues Hakkarainen.

Combining NO2 and CO2 observations enables the detection of CO2 emission sources in South Africa. See for example the plumes from Matimba Power Station.

Satellite observations available with such detail open new opportunities for societal applications, including urban and industrial emission monitoring. For example, satellite observations have been already used in the cleantech sector in order to evaluate the efficacy of their technology in reducing polluting emissions from metal smelting”, comments Iolanda Ialongo, from the Finnish Meteorological Institute. “Future greenhouse gas missions should be designed with a wider coverage than what is currently available, in order to improve the capabilities of monitoring man-made CO2 emissions”.

The results are achieved within the DACES project, which focuses on detecting anthropogenic CO2 emissions sources by exploiting the synergy between satellite-based observations of short-lived polluting gases (such as NO2) and greenhouse gases.

The full publication by Hakkarainen and co-authors can be found at the following link:


Summer School on Very Finnish Inverse Problems

The Finnish Centre of Excellence in Inverse Modelling and Imaging and Finnish Inverse Problems Society (FIPS) are proud to organize a Summer School on inverse problems on June 3-7, 2019.

The event will take place at the Kumpula Campus of University of Helsinki, Finland.

The content is primarily intended for PhD students and postdoctoral researchers in mathematics or physics working in the field of inverse problems.

Below is the list of confirmed speakers. There will be a few more coming up.


Tatiana Bubba (University of Helsinki): X-ray tomography
Janne Hakkarainen (Finnish Meteorological Institute): Kalman filter
Ville Kolehmainen (University of Eastern Finland): Bayesian inversion and MCMC
Marko Laine (Finnish Meteorological Institute): Markov Chain Monte Carlo (MCMC) methods
Mikko Salo (University of Jyväskylä): Applications of microlocal analysis to inverse problems

Short talks:

Hanne Kekkonen (University of Cambridge): TBA
Matti Lassas (University of Helsinki): Geometric inversion
Aku Seppänen (University of Eastern Finland): TBA
Samuli Siltanen (University of Helsinki): X-ray tomography
Antti Solonen (Leanheat Oy, LUT University): Hierarchical Bayesian models for marine vessels
Johanna Tamminen (Finnish Meteorological Institute): Satellite remote sensing
Tanja Tarvainen (University of Eastern Finland): Tomographic imaging with light and sound

To register, please send email to “at” Registration fee is 60 euros. The registration fee can be paid in cash at the beginning of the course, or to the following bank account:
Account owner: Suomen inversioseura
IBAN number: FI72 1012 3000 2079 18
Y-tunnus 2008830-2
Reference number: 600 4

Deadline for registration: April 30, 2019.