Satellites reveal air pollution from the world’s largest copper mines

Satellite observations highlight nitrogen oxide emissions coupled with copper production 

 

Copper plays a crucial role in the global transition to a sustainable economy, serving as a key component in electric vehicles, solar panels, and wind turbines. However, copper mining also poses environmental and social challenges that must be addressed responsibly. Assessing the mining industry's performance and environmental impact is essential for tracking progress toward sustainable development.

 

A new study, published in Environmental Research Letters, utilizes satellite observations of nitrogen dioxide (NO₂) to estimate nitrogen oxide (NOx) emissions over 14 of the world’s largest open-pit copper mines. The monitored sites include major copper mines in the United States, Chile, Peru, Mexico, and Zambia. The emissions mostly originate from the diesel-powered mobile fleet operating over the mines. The highest emissions were observed at the Morenci copper mine in Arizona, USA. The study found that NOx emissions are rising at many sites, particularly in South America. In contrast, emissions in the Zambian mines appear to be declining, likely due to increased electrification of mining equipment. The emissions increase with increasing copper production and moved material volumes.

With growing pressure for the mining industry to align with environmental, social, and governance (ESG) principles, independent monitoring is crucial. “Currently, most sustainability reporting in the mining sector relies on self-disclosures by companies, which can be inconsistent and incomplete. Satellite observations provide an independent, timely, and transparent way to track emissions,” explains Dr. Iolanda Ialongo, senior researcher and lead author of the study.

Satellite observations can also detect sudden changes in mining operations, such as shifts in fossil fuel usage due to fleet electrification, thereby supporting emission reduction strategies. Satellite-based assessments are especially valuable in regions lacking other monitoring systems, offering actionable data for environmental authorities, non-governmental organizations, and local communities.

REFERENCE 
Ialongo I., Virta H., Hakkarainen J., Özcan C., Ranta M., and Zieleniewski S. (2025): Unveiling nitrogen oxide emissions from open-pit copper mines through satellite observations, Environ. Res. Lett. 20 034041 https://doi.org/10.1088/1748-9326/adb767

Linear Integrated Mass Enhancement

I’m pleased to share that our paper, “Linear Integrated Mass Enhancement: A method for estimating hotspot emission rates from space-based plume observations,” has been published in Remote Sensing of Environment.

In this paper, we propose a new methodology for plume inversion emission estimation termed linear integrated mass enhancement (LIME). As the name implies, this approach is based on the integrated mass enhancement (IME) method and on the linear relationship between IME and the distance from the source. The proposed approach accounts for the information coming from different portions of the plume, and it can be seen as a “combination” of the cross-sectional flux (CSF) method and IME. The method offers a straightforward way to estimate the source strength by determining the slope of the linear fit.

We test the LIME approach with both real (OCO-3, S5P/TROPOMI, Sentinel-2) and simulated (MicroHH, SMARTCARB) satellite data. We apply the method to the simulated carbon dioxide (CO2) observations for the upcoming CO2M mission over the Matimba and Jänschwalde power stations with known source rates. We use the OCO-3 data to estimate the CO2 emissions originating from the Bełchatów power station in Poland (between 72 and 103 ktCO2/d). We also estimate the emissions from two methane (CH4) leaking sites in Algeria based on S5P/TROPOMI (77 and 47 tCH4/h for two days) and Sentinel-2 (7.7 tCH4/h) observations. Finally, we apply the LIME method to the Sentinel-2 retrievals from a controlled CH4 release in Arizona.

Across all case studies, the LIME emission estimates are in agreement with the expected values. The LIME estimates are also aligned with the state-of-the-art IME emission estimates, which are calculated as byproducts in the LIME emission estimation process.

Citation:

Janne Hakkarainen, Iolanda Ialongo, Daniel J. Varon, Gerrit Kuhlmann, and Maarten C. Krol: Linear Integrated Mass Enhancement: A method for estimating hotspot emission rates from space-based plume observations, Remote Sensing of Environment, Volume 319, 2025, https://doi.org/10.1016/j.rse.2025.114623.

Emission Observatory – Pilot for Africa

Climate change, driven by increasing atmospheric concentrations of anthropogenic greenhouse gases (GHGs), is one of the greatest threats of our time. Space-based observations offer new opportunities for improving the completeness and transparency of emission reports as they provide objective observations over areas where other information is inaccurate or not available.

Over the past decade, satellite-based measurements of greenhouse gases have transformed the estimation of emission rates from anthropogenic hotspots. New satellite observations of emission plumes from point sources have created opportunities to use simpler and more computationally efficient methods for estimating emissions. International accords like the 2015 Paris Agreement have played a major role in driving research in this area. Many space agencies, organizations, and private companies are now developing new GHG satellite missions and constellations to observe plumes and support future monitoring of GHG emissions.

To obtain emission estimates from atmospheric concentrations, mathematical inverse modeling methods are needed. The Finnish Meteorological Institute is dedicated to developing new methods for data-driven emission estimation that do not require complex atmospheric modeling. In particular, the team has developed several new plume inversion techniques for various recent satellite missions. As part of user engagement activities, the team has piloted a new service for the African continent, where ground-based information has traditionally been less available.

The Emission Observatory – Pilot for Africa platform is an interactive map service for monitoring anthropogenic GHG and air pollution hotspots in Africa using satellite observations and state-of-the-art emission estimation methods. Specific focus areas include cities and megacities, the mining sector (particularly critical minerals needed for the green transition), energy production (e.g., power plants in South Africa's Highveld region), and the oil and gas industry (especially regarding fugitive methane emissions and gas flaring). The service is set to inform decision makers, environmental authorities, citizens and industry about emission sources and their spatio-temporal variability, specifically over the African continent. The information provided through the platform are tailored to the users’ needs and feedback. The platform is based on publicly available observations from the EU’s Copernicus Sentinel fleet and NASA’s Earth observation program. 

User and stakeholders of the Emission Observatory – Pilot for Africa service can engage and participate in the service implementation through a co-design process.

If you are interested in and would like to benefit from this service and methods, please contact us: emissionobservatory@fmi.fi

Link to the service: https://www.emissionobservatory.org

Number of primes between n and 2n?

Chebyshev said it, but I'll say it again; There's always a prime between n and 2n.

But how many primes there are between n and 2n?

The prime number theorem (PNT) says that π(n) ~ n/ln(n).

So, the number of primes between n and 2n is roughly π(2n)- π(n) ≈ 2n/ln(2n) - n/ln(n).

Now, ln(2n) = ln(2) + ln(n) which is dominated by ln(n) when n is large.

Hence, we obtain π(2n)- π(n) ≈ 2n/ln(n) - n/ln(n) = (2n-n)/ln(n) = n/ln(n).

Of course, a much better approximation is given by the logarithmic integral 

And here is the plot:

Ilmatieteen laitos valmistautuu Copernicus CO2M -missioon

Vuonna 2015 solmitun Pariisin ilmastosopimuksen myötä ihmisten aiheuttamien kasvihuonekaasupäästöjen monitorointi on noussut entistä tärkeämmäksi. Tämän takia Euroopan komission maanseurantaohjelma Copernicus on valmistelemassa uutta CO2M-missiota, jonka tarkoituksena on erityisesti keskittyä ihmisten aiheuttamien hiilidioksidipäästöjen seurantaan. Satelliittikonstellaation on tarkoitus koostua kahdesta tai useammasta satelliitista, jotka havainnoivat hiilidioksidia (CO₂) ja typpidioksidia (NO₂) 250 km laajuisella kaistalla 4 km² spatiaalisella resoluutiolla. Ensimmäinen satelliitti on tarkoitus laukaista vuonna 2026.

Ilmatieteen laitoksen vetämässä, vasta julkaistussa tutkimuksessa [1] datapohjaisia päästöestimointimenetelmiä sovellettiin Sentinel 5P -satelliitin TROPOMI-mittalaitteen typpidioksidihavaintoihin. Tutkimuksen tavoitteena oli tutkia Matimba/Medupi-kivihiilivoimaloiden päästöjä Etelä-Afrikassa. Koska voimaloiden päästö on typpimonoksidin ja typpidioksidin summa (NO_x = NO + NO₂) ja satelliitti mittaa pelkkää typpidioksidia, niin datapohjaiset päästöarviointimenetelmät tarvitsevat skaalauskertoimia, jotta NO₂-pohjainen päästöarvio voidaan muuttaa oikeaan muotoon.  Tutkimuksessa osoitettiin, että tarvittavat skaalauskertoimet riippuvat sekä käytetystä päästöestimointimenetelmistä, että alueesta mistä päästöinformaatio tulee.

”Tutkimuksessa käytettyjen MicroHH-simulointien perusteella johdetut skaalauskertoimet ovat huomattavasti (yli 50 %) korkeammat kuin kirjallisuudessa yleisesti käytetyt tyypilliset arvot todellisten NO₂-havaintojen kanssa,” julkaistua tutkimusta vetänyt Janne Hakkarainen kertoo.

Ilmatieteen laitos oli mukana EU:n H2020-ohjelman CoCO2-hankkeessa. Hankkeen keskeisenä tavoitteena oli valmistautua tuleviin CO2M-mittalaitteen havaintoihin. Ilmatieteen laitoksen vetämässä työpaketissa kehitettiin datapohjaisia menetelmiä voimakkaiden päästölähteiden kuten kivihiilivoimaloiden ja kaupunkien päästöestimointiin. Tavoitteena oli myös verrata eri menetelmiä keskenään käyttäen hyväksi synteettisiä mittauksia.

Työpaketin seurauksena syntyi kolme uutta tieteellistä julkaisua aiemman Ilmatieteen laitoksen vetämän menetelmäpaperin lisäksi. Sveitsiläisen Empa-instituutin vetämässä artikkelissa [2] rakennettiin ddeq Python-kirjasto, jolla voidaan satelliittikuvista laskea pistelähteiden päästöt. Ranskalaisen LSCE-instituutin vetämässä julkaisussa [3] eri menetelmiä verrattiin keskenään.

 

Viitteet:

[1] 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, https://doi.org/10.1016/j.apr.2024.102171, 2024.

[2] Kuhlmann, G., Koene, E. F. M., Meier, S., Santaren, D., Broquet, G., Chevallier, F., Hakkarainen, J., Nurmela, J., Amorós, L., Tamminen, J., and Brunner, D.: The ddeq Python library for point source quantification from remote sensing images (Version 1.0), Geoscientific Model Development, https://doi.org/10.5194/egusphere-2023-2936, 2024.

[3] Santaren, D., Hakkarainen, J., Kuhlmann, G., Koene, E., Chevallier, F., Ialongo, I., Lindqvist, H., Nurmela, J., Tamminen, J., Amoros, L., Brunner, D., and Broquet, G.: Benchmarking data-driven inversion methods for the estimation of local CO₂ emissions from XCO₂ and NO₂ satellite images, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-241, 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 Rep 13, 14954 (2023). https://doi.org/10.1038/s41598-023-42118-w

Two weeks in China

Hello,

some while a go me and my buddy Prof. Dongxu Yang got a joint Finland-China cooperation project together. He got the money from the Chinese Academy of Sciences (CAS) to travel to Finland and I got the money from the Research council of Finland to travel to China.

During the COVID-19 it was difficult to travel. But finally, after a long wait, I got to travel to China in September 2023. The travel plan was quite simple: The first week I would be visiting Dongxu at the Institute of Atmospheric Physics (IAP), CAS, and the second one we would be in the ESA-MOST DRAGON symposium in Inner Mongolia.

The first week was full of interesting discussions with many different people. For example, I got to see the drone equipment and we had discussions how they are planning to estimate CO₂ emissions from power plants and validate satellite-based results. They plan to use cross-sectional flux methods, as I have done in my own research. I was happy to see that they use sensors from the Finnish Vaisala company.

I also got to speak about my work on the IAP seminar. After the seminar, I had some nice discussion about my work with Kai Wu who has previously worked on MicroCarb project at the University of Edinburgh. Actually, surprisingly many of the people I met, have worked there. At IAP they have many seminars. On the same day that I gave my seminar presentation, we went to see some AI/ML seminar by some famous Chinese scientist. The seminar was in Chinese, so I couldn’t follow much even though the slides were in English.

The week was also full of interesting dinners with interesting people and some sightseeing of course. I also got the visit the Earth Lab with Dongxu. During my visit the institute also had its 95th birthday and during weekend they had big celebration at the Earth Lab.

On Sunday evening me, Dongxu and Prof. Liu traveled together on a high-speed train to Inner Mongolia’s capital Hohhot where the DRAGON symposium takes place. The train stations in China seem like airports and trains like airplanes. In general, on a technological level, it seems that Chinese people are ahead of Europeans. For example, everything is paid and done on a mobile app.

On Monday, Prof. Liu organized a Workshop on China-EU GHGs measurement from Space. I also got to present my work and we had discussions on co-operations between European Copernicus CO2M and China’s TanSat-2 missions.

Tuesday marked the official opening of the DRAGON Symposium and the symposium started with some traditional Inner Mongolian music. During the poster session I had interesting discussions with Qiangian Zhang, who has done similar work that I have. I also presented a paper poster.

Wednesday was our DRAGON project main day, and Prof. Liu presented the project very well. We also prepared a summary slide of our work that Ronald van der A presented at the final session summaries. Our recommendations to ESA and MOST were:

1. High-level co-operation between TanSat-2 and Copernicus CO2M missions to be organized by ESA and MOST
2. TanSat-2 to be included as an ESA Third Party Mission

On Friday afternoon I took a train back to Beijing with a fantastic duo from IAP/CAS: Lu Yao and Yuli Zhang. After the train arrived at Beijing, they were kind enough to put me in taxi on towards the airport hotel. On Saturday morning I started my journey back to Europe and on Sunday at 1:30 a.m. I arrived home. Then I rested.

Thank you!

Janne

Building a Bridge: Estimating Carbon Dioxide Emissions Using Satellites

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 new publication characterizes CO₂ emissions using data from NASA’s Orbiting Carbon Observatory-3 (OCO-3) and European Copernicus Sentinel-5P/TROPOMI.

 

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: https://doi.org/10.1088/1748-9326/acb837

Optical flow

Hi Guys,

when I was visiting the inverse problems research group at the University of Helsinki I learned about the method called optical flow. We used this method in out paper on dynamic X-ray data.

Recently, I've been studying how the optical flow method could be applied to my current research on CO₂ emission estimation.

Of course I had to try the optical flow method also on myself

Note that this method is not based on machine learning.

Cheers,

Janne

Uusi menetelmä ihmisten aiheuttamien hiilidioksidipäästöjen seurantaan avaruudesta

Uusi menetelmä ihmisten aiheuttamien hiilidioksidipäästöjen seurantaan avaruudesta

 

Vuonna 2015 solmitun Pariisin ilmastosopimuksen myötä ihmisten aiheuttamien kasvihuonekaasupäästöjen monitorointi on noussut entistä tärkeämmäksi. Tämän johdosta Euroopan komission maanseurantaohjelma Copernicus on valmistelemassa uutta CO2M-missiota, jonka tarkoituksena on erityisesti keskittyä ihmisten aiheuttamien hiilioksidipäästöjen seurantaan. Satelliittikonstellaation on tarkoitus koostua kahdesta tai useammasta satelliitista, jotka havainnoivat hiilidioksidia (CO₂) ja typpidioksidia (NO₂) 250 km laajuisella kaistalla 4 km² spatiaalisella resoluutiolla. Ensimmäinen satelliitti on tarkoitus laukaista vuonna 2025.

Simuloituja CO2M-satelliitin XCO₂-havaointoja. Kuva: Gerrit Kuhlmann, Empa.

Julkaistussa tutkimuksessa kehitettiin uusi divergenssimenetelmä, jonka avulla voidaan laskea hiilidioksidin ja typen oksidien (NO_x) päästöt kaupungeista ja voimaloista. Menetelmää sovellettiin mallisimulaatioista saatuihin synteettisiin CO2M-havaintoihin (esitetty kuvassa). Koska CO₂-havaintojen tausta ja kohina ovat suuria verrattuna havaittuihin päästölisäyksiin, julkaisussa sovellettiin myös erilaisia kohinansuodatusmenetelmiä. Divergenssimenetelmä saadut päästöestimaatit ovat linjassa odotettujen arvojen kanssa. Julkaisussa keskusteltiin myös hiilidioksidipäästöjen laskemisesta NO_x-päästöistä käyttäen hyväksi suoraan satelliittihavainnoista laskettua NO_x:CO₂-suhdetta. Yleisesti tutkimuksessa havaittiin, että divergenssimenetelmä antaa hyvän vaihtoehtoisen tavan laskea CO₂-päästöt verrattuna esimerkiksi inversiomallinnusmenetelmiin ja menetelmiin, jotka laskevat päästöt yksittäisistä satelliittikuvista.

 

Tutkimus on tehty yhteistyössä Ilmatieteen laitoksen ja Sveitsiläisen Empa-instituutin kanssa. Sen rahoittamiseen ovat osallistuneet EU:n H2020-projekti CoCO2 ja Euroopan avaruusjärjestö ESA:n rahoittama projekti DACES, sekä Suomen Akatemia (CitySpot, ACCC, Inversiomallinnuksen ja kuvantamisen huippuyksikkö).

Viite: 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 Sensing, vol 3, 2022, doi:10.3389/frsen.2022.878731, Linkki

Anthropogenic Emission Monitoring with the Copernicus CO2 Monitoring Mission

Hi guys,

I am pleased to say that our manuscript was accepted today for the CO2M special issue “Anthropogenic Emission Monitoring with the Copernicus CO2 Monitoring Mission” in Frontiers in Remote Sensing.

You can find the special issue here: https://www.frontiersin.org/research-topics/20546/anthropogenic-emission-monitoring-with-the-copernicus-co2-monitoring-mission#articles

Our paper is called “Analyzing local carbon dioxide and nitrogen oxide emissions from space using the divergence method: An application to the synthetic SMARTCARB dataset” and it is joint work between Finnish Meteorological Institute and Empa, Switzerland. The abstract is already online: https://www.frontiersin.org/articles/10.3389/frsen.2022.878731/abstract

I will write more about the paper when it is officially published!

Stay tuned!

Janne

Hi guys,

yesterday I was thinking what would happened if one would start Conway's Game of Life from the Ulam Spiral...

-Janne

Emissions from Siberian oil fields detected from space

Hi guys,

I wanted to advertize our new paper on Atmospheric Environmemt: X "Satellite-based estimates of nitrogen oxide and methane emissions from gas flaring and oil production activities in Sakha Republic, Russia." It is a very nice collaborative effort between natural and social sciences led by Iolanda. The results are strongly related to our ESA-funded DACES project.

In the paper there are lot of interesting analysis on nitrogen oxide and methane emissions in Tas-Yuryakh and Talakan oil fields. One of my favorite pictures is the one below illustrating methane anomalies as observed S5P/TROPOMI over Talakan. The patterns of the site are clearly visible.

TROPOMI/S5P methane enhancement over Talakan oil field. Credits: Ialongo et al., (2021), CC BY 4.0

To have more information please see this article in FMI-SPACE or in Finnish here. Please also check the full paper below:

Ialongo, I., Stepanova, N., Hakkarainen, J., Virta, H., Gritsenko, D.: Satellite-based estimates of nitrogen oxide and methane emissions from gas flaring and oil production activities in Sakha Republic, Russia, Atmospheric Environment: X, Volume 11,  https://doi.org/10.1016/j.aeaoa.2021.100114, 2021.

Cheers,

Janne

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 CO₂emissions 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).

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.

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.

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 CO₂and NO₂ plumes. The mean NO_x-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

Ihmisperäisiä hiilidioksidipäästöjä metsästämässä – apurina satelliitit

Ilmatieteen laitoksella kehitettiin uusi menetelmä laskea yksittäisten päästölähteiden, kuten kaupunkien ja voimaloiden, NOₓ/CO₂-suhde avaruudesta käsin. Tuloksia voidaan hyödyntää myös hiilidioksidipäästöjen arvioinnissa. Uutta menetelmää sovellettiin Etelä-Afrikassa sijaitsevaan Matimba-hiilivoimalaan, joka on yksi maailman suurimmista.

Matimba-hiilivoimala Etelä-Afrikassa. Wikimedia commons. CC BY-SA 3.0

Vuonna 2015 solmitun Pariisin sopimuksen myötä ihmistoiminnasta peräisin olevien kasvihuonekaasupäästöjen rooli tutkimuksessa on noussut yhä tärkeämmäksi, sillä päästöjä ja niiden vähennyksiä halutaan seurata. Esimerkiksi Euroopan komissio suunnittelee uutta satelliittipohjaista CO2M-missiota ihmisperäisten hiilidioksidipäästöjen seuraamiseen osana Copernicus-maanseurantaohjelmaansa.

Ilmatieteen laitoksella on tutkittu ihmisperäisiä kasvihuonekaasuja avaruudesta käsin vuodesta 2016 alkaen. Tutkimuksessa on hyödynnetty erityisesti vuonna 2014 laukaistua NASAn OCO-2-satelliittia, joka on edelleen paras mittalaite tähän työhön. Ihmisperäisten hiilidioksidipäästöjen kartoittamisen kannalta sen kapea mittauskaista asettaa kuitenkin haasteita.

Eräs keskeisistä ongelmista ilmakehätieteissä on laskea päästöt yksittäisistä päästölähteistä kuten kaupungeista ja voimaloista. Tämä on erityisen haastavaa hiilidioksidin (CO₂) kohdalla, kun taas typen oksidien NOₓ-päästöjä on monitoroitu satelliiteista lähes rutiininomaisesti jo 1990-luvulta alkaen. Ilmanlaadun kannalta NOₓ- ja CO₂-päästöjen välinen suhde kertoo käytetyn tekniikan puhtaudesta.

Juuri julkaistussa tutkimuksessa kehitettiin uusi menetelmä, jolla voidaan laskea NOₓ/CO₂-suhde avaruudesta käsin. Näin laskettua suhdetta voidaan hyödyntää myös, jos halutaan kääntää NOₓ-päästöt hiilidioksidipäästöiksi. Tutkimuksessa tätä menetelmää sovellettiin Etelä-Afrikassa sijaitsevaan Matimba-hiilivoimalaan. Se on tutkimuksen kannalta erinomainen koelaboratorio, sillä se on voimakas pistemäinen päästölähde ja suhteellisen etäällä muista päästölähteistä.

Tutkimuksessa hyödynnettiin vuonna 2017 laukaistun eurooppalaisen Sentinel 5 Precursor S5P-satelliitin tekemiä mittauksia, jotka mahdollistavat ensi kertaa yksittäisten typpidioksidipilvien (NO₂-pilvet) kartoittamisen satelliitista käsin. Tutkimuksessa yhdistettiin S5P-satelliitin havaitsemat NO₂-pilvet ja OCO-2-satelliitin CO₂-havainnot. Vuosilta 2018–2020 löydettiin yhteensä 14 satelliitin ylilentoa, jossa kapealla kaistalla mittaavan OCO-2-satelliitin havainnot kyettiin kytkemään S5P-satelliittiin mittaamiin NO₂-pilviin.

Kuvassa S5P ja OCO-2-satelliittien havaintoja vuosilta 2018–2020 yhdistettynä. Matimba-hiilivoimala on merkitty kuvaan punaisella kolmiolla. Hiilivoimalasta peräisin olevat NOₓ-päästöt näkyvät kuvassa punaisesta kolmiosta lähtevänä pilvenä lähialueella. OCO-2-satelliittin tekemät mittaukset hiilidioksidista näkyvät kapeina viivoina kuvassa. Nämä havainnot yhdistämällä voidaan laskea NOₓ/CO₂-suhde. Kuva: Hakkarainen et al. 2021. CC BY 4.0.

Ilmakehää mallinnettiin FLEXPART-mallilla ja tuloksena saatiin Matimba-hiilivoimalan NOₓ/CO₂-suhteeksi (2.6 ± 0.6) × 10^-3 ja hiilidioksidipäästöiksi noin 60 kilotonnia päivässä, joka on suuruusluokaltaan noin puolet koko Suomen hiilidioksidipäästöistä. Tutkimuksessa lasketut arviot ovat yhteneviä aikaisempien päästöinventaarioiden (esim. ODIAC) tulosten kanssa.

Tutkimusta on tehty erityisesti Euroopan Avaruusjärjestö ESAn rahoittamassa DACES-projektissa, josta voit lukea lisää projektin verkkosivuilta.

Viite:

Janne Hakkarainen, Monika E. Szeląg, Iolanda Ialongo, Christian Retscher, Tomohiro Oda, and David Crisp: Analyzing nitrogen oxides to carbon dioxide emission ratios from space: A case study of Matimba Power Station in South Africa, Atmospheric Environment: Volume 10, 2021.

Lue tieteellinen artikkeli täältä: https://doi.org/10.1016/j.aeaoa.2021.100110

Analyzing nitrogen oxides to carbon dioxide emission ratios from space: A case study of Matimba Power Station in South Africa

Hi guys,

I just wanted to say that we have a new paper on Atmospheric Environment: X

The paper Analyzing nitrogen oxides to carbon dioxide emission ratios from space: A case study of Matimba Power Station in South Africa was written by myself, Iolanda Ialongo, Monika Szeląg, Christian Retscher, Tomohiro Oda, and David Crisp.

Highlights:

• A new methodology to derive source-specific NO_x-to-CO₂ emission ratios.
• The method is applied for TROPOMI and OCO-2 satellite observations.
• The mean emission ratio of (2.6±0.6)×10⁻³ is obtained for Matimba Power Station.
• The annual CO₂ emissions for Matimba are ∼60 kt/d.
• The emission estimates are consistent with existing inventories such as ODIAC.

The Journal Pre-proof version is already available online: https://doi.org/10.1016/j.aeaoa.2021.100110

I will write more about this paper later.

Stay tuned!

Janne

Pandigital π

Hah!

Yesterday I was watching this Numberphile video

   

and like Dr. James Grime, I did not like the pandigital formula for π. So I decided to play a little with pen and paper, and found the following

I think it is quite neat. Of course, I knew beforehand that 355/113 approximates π quite well, up to 6 decimal places. Actually, it is called Milü. 

Cheers,

Janne

Faktoja ilmastonmuutoksesta: hiilinielu vai hiilivarasto?

Monilla tuntuu menevän käsitteet hiilinielu ja hiilivarasto lahjakkaasti sekaisin. Erityisen harmilliselta tämä tuntuu, jos kyseessä on ns. vakavasti otettava tutkija.

Fakta 1. Toisin kun yleensä luullaan vanhat metsät kuten Amazonin sademetsä ei ole voimakas hiilinielu. Nuoret metsät (alle 140 vuotta) taas ovat. Yleistajuisesti voi PNAS-lehdessä julkaistusta tutkimuksesta voi lukea täältä.

(Myös muut tutkimustulokset, kuten omani, ovat päätyneet samaan johtopäätökseen, mutta se ei nyt varsinaiset liity tähän.)

Tämä ei ole oikeastaan yllättävää. On selvää, että hyvin vanha metsä (yli 150 vuotta) ei enää toimi hiilinieluna vaan voi jopa toimia päästölähteenä. Toisaalta nuori parhaassa kasvuiässä oleva metsä toimii voimakkaana hiilinieluna eli se poistaa ilmakehästä hiiltä. Vanha metsä voi toki olla suurempi hiilivarasto kuin nuori metsä, mutta nieluna se ei enää toimi. Jos siis halutaan, että metsät toimivat hiilinieluina olisi oltava mahdollisimman paljon 20–80-vuotiasta metsää.

Fakta 2. Hiilinielu ei ole hiilivarasto. Nielu on prosessi, toiminta tai mekanismi, joka sitoo kasvihuonekaasun, aerosolin tai niiden esiasteen ilmakehästä. Lähde taas tarkoittaa prosessia, toimintaa tai mekanismia, joka vapauttaa kasvihuonekaasun, aerosolin tai niiden esiasteen ilmakehään. Hiilivarasto taas kertoo yksinkertaisesti paljonko johonkin on varastoitunut hiiltä. Yksinkertaisesti voi ajatella, että puuliiterissä olevat klapit ovat hiilivarastossa, mutta muuttuvat päästöiksi saunan pesässä. Kun saunan vieressä oleva puu kasvaa (ja poistaa ilmakehästä hiiltä), niin se toimii nieluna.

Fakta 3. Hiilivaraston muutos ei ole hiilinielu. Tehdään ajatuskoe. Käyt lähimetsässä ja poimit metsästä kilogramman edestä hiiltä. Nyt metsän hiilivarasto on pienentynyt kilogramman verran, mutta ilmakehä ei tiedä tästä mitään eli et ole aiheuttanut päästöjä. Vastaavasti jos viet hiilen takaisin metsään, niin metsä ei ole ymmärrettävästi toiminut ilmakehän hiilinieluna. Jos veistät löytämästä puusta lusikoita, se toimii hiilivarastona (ei nieluna!) ja jos taas poltat löytämäsi puun, aiheutat päästöjä.

Bonus. Puut eivät tulevat maasta vaan ilmasta kertoo Richard Feynman.

Virtual Inverse Days 2020

Virtual Inverse Days 2020

 

University of Helsinki and Finnish Meteorological Institute co-organized 26^th 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 60^th 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