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: https://doi.org/10.1016/j.aeaoa.2021.100110

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: https://www.youtube.com/channel/UCqSbbWIqt9ZhWbAlJgEOGZg

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: https://www.fips.fi/id2020.php

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: https://www.mdpi.com/2072-4292/11/7/850

Source: https://eo4society.esa.int/2019/10/24/anthropogenic-co2-emission-sources-detected-from-space/

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.

Minicourses:

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 summer.school “at” fips.fi. 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
SWIFT/BIC Code: NDEAFIHH
Y-tunnus 2008830-2
Reference number: 600 4

Deadline for registration: April 30, 2019.

Inverse problems on remote sensing tackled at FMI

FMI-SPACE hosted a Workshop on Inverse Problems and Uncertainty Quantification in Satellite Remote Sensing in 10–12 October, 2018. The workshop gathered together international experts on remote sensing and related mathematical and statistical inverse problems.

Advances in atmospheric remote sensing are profoundly linked to finding efficient solutions to inverse problems. In particular, the workshop addressed in several contributions novel approaches for satellite retrievals of carbon dioxide, especially regarding the Nasa Orbiting Carbon Observatory -2 (OCO-2) mission. Prof. Heikki Haario, the lead organiser of the workshop, emphasises the importance of collaboration between researchers from different fields in this inherently multidisciplinary effort.  The presentations covered several aspects of the OCO-2 mission, and novel methods for high dimensional and high-CPU problems encountered in remote sensing in general.

The workshop was organised jointly by the FMI and Lappeenranta University of Technology teams of the Academy of Finland Centre of Excellence in Inverse Modelling and Imaging. The Centre of Excellence started in January 2018 and continues for eight years. Within the Centre of Excellence, the scientific goal of the FMI team, led by Prof. Johanna Tamminen, is to improve the interpretation of satellite remote sensing of greenhouse gases and air quality by developing and applying novel mathematical and statistical methods of uncertainty quantification to satellite remote sensing. The ultimate goal is to develop improved methods for estimating sources and sinks of greenhouse gases by utilising satellite observations.

The workshop attracted close to 30 participants, including leading international experts from the Nasa Jet Propulsion Laboratory, Massachusetts Institute of Technology, University of Montana, Case Western Reserve University, University of Warwick, and University of Monash.