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.

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.